{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "'''\n",
    "【课程1.7】  相关性分析\n",
    "\n",
    "分析连续变量之间的线性相关程度的强弱\n",
    "\n",
    "图示初判 / Pearson相关系数（皮尔逊相关系数） / Sperman秩相关系数（斯皮尔曼相关系数）\n",
    "\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy import stats\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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3eO+/D1wLLALeVrnWxycJ5+rZct7Fd6IPAUxrWF0ScpSLlSzKkTyWskRB1epE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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb1ce470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 图示初判\n",
    "# （1）变量之间的线性相关性\n",
    "\n",
    "data1 = pd.Series(np.random.rand(50)*100).sort_values()\n",
    "data2 = pd.Series(np.random.rand(50)*50).sort_values()\n",
    "data3 = pd.Series(np.random.rand(50)*500).sort_values(ascending = False)\n",
    "# 创建三个数据：data1为0-100的随机数并从小到大排列，data2为0-50的随机数并从小到大排列，data3为0-500的随机数并从大到小排列，\n",
    "\n",
    "fig = plt.figure(figsize = (10,4))\n",
    "ax1 = fig.add_subplot(1,2,1)\n",
    "ax1.scatter(data1, data2)\n",
    "plt.grid()\n",
    "# 正线性相关\n",
    "\n",
    "ax2 = fig.add_subplot(1,2,2)\n",
    "ax2.scatter(data1, data3)\n",
    "plt.grid()\n",
    "# 负线性相关"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-100.107196</td>\n",
       "      <td>151.774404</td>\n",
       "      <td>75.914739</td>\n",
       "      <td>-40.279130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-45.713333</td>\n",
       "      <td>-29.882627</td>\n",
       "      <td>182.479549</td>\n",
       "      <td>61.600886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-4.293934</td>\n",
       "      <td>-68.730078</td>\n",
       "      <td>-102.025975</td>\n",
       "      <td>202.510936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>55.385126</td>\n",
       "      <td>-171.545669</td>\n",
       "      <td>4.908165</td>\n",
       "      <td>120.779550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-72.515302</td>\n",
       "      <td>118.986304</td>\n",
       "      <td>0.212236</td>\n",
       "      <td>61.995667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            A           B           C           D\n",
       "0 -100.107196  151.774404   75.914739  -40.279130\n",
       "1  -45.713333  -29.882627  182.479549   61.600886\n",
       "2   -4.293934  -68.730078 -102.025975  202.510936\n",
       "3   55.385126 -171.545669    4.908165  120.779550\n",
       "4  -72.515302  118.986304    0.212236   61.995667"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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H00hJ85aAv6KiQlNM169fz5kzZ6irq/PpaqM/T05ODiNHjqSgoEBTbGtqaqit\nrcVkMvHiiy8CMG3aNMxmM5MmTWLv3r3MnTuXw4cPU1VVxaRJk5gyZYrP6/MVfGX0TPqrJF4uOU71\nuD93Y8eO5eDBgx6VRCMCzYLiPoY899xznDhxggsXLmC1WmlsbGTp0qWG+XNVv2qn04kQgr/+9a/U\n1taSmJjI0KFDDfPoul+vPu9uIC804ZB9I1RIBbcfYbPZvlRuK4FrA9hzN7C0exol6RF8BSZ4GwAD\nHfACSV+zdOlSvvvd71JRUcG+ffsoKCggKSmJkpISLfjHve02m42vfe1rvPnmm9TV1WEymdiwYQOn\nT5/mxIkTLlYuT9et+tqBcZGG7ra09lcrSU+lQjNS0rwl4F+5cqWmmK5YscJn4Jj7edLT07FYLLS3\nt2M2m3E4HEyaNIlZs2Z1KhihKAqxsbG8++67msVfURS+//3vk5yc7JfC0dUS1p7uWbhmW3AnWCu0\n/r6pSuLMmTPZvXu3z/sQaMYHI6txZGQk//Vf/8Uf//hHFi9erAWOub/03njjjdxyyy3s3r2bZ599\nFpPJRFRUFKdOneKVV17B6XTS0tKirR54u059EK96HX3Jet+bSAW3X3Itl9yK/UW6KIQ73gZnf4Kz\nAiGQ9DUpKSmkpKQwZMgQ9u3bR1JSEoMGDeLMmTPU19cDnUtgFhcX43Q6mT59OuPGjaOwsNDFgqtO\n4p6CcuCS0jNlyhSfCn93VVXqr1aS7k775Kt4grtSGB8fD0BLS4ummEZFRXVSKjy5NajH37RpEzU1\nNZhMJkwmEx0dHTz11FNacCO4yogQgtzcXJcsHZMnT+bKK6/0y4LaHZb+QPqmL7ox6OmKFVpfnKWl\npYXU1FQWL17MlClTPL6QZ2dne62AZ4SR1dhisfDZZ5+xZ88ew+31+XCrq6t5/vnnOX36NFFRUVy8\neJE1a9ZgMpkYMWJEUHm3o6KiKC0tvays996QCq5E0g/wNvmHyqLTlfQ1ycnJpKenU1JSom27atUq\nzGYzM2fOpKSkhE2bNlFbW0thYaE2sRw6dIiPP/6YZ599lpiYGOLj4ykuLgbQUu8YWcJ2797tUjHO\nm8IfqKXVU67NvqoshJLutnz7s3SvkpqaSk1NjcsycUdHB4sXL9ZyD3tza9C/VNXW1gIwceJE6uvr\nWbNmjccyrEbHs9vtlJaWMnLkSNrb211+M1K29fLSVflTcY+Snzhxoscoeb3lui/Jblet0O75kJcs\nWYLD4eCnWMfkAAAgAElEQVT8+fMUFxdr90M/ZpWXlzNy5EgqKio4e/Yst9xyC/BVBTxf90ftw7q6\nOqqqqrQMKmVlZS5ZPNxfet3z5gLk5uYSExPD1q1bA867rV5rR0dHWFvvQ4qvKLTL4UM/yaLQ89kQ\nZBaFQOnuyHZ9hGwgGQX8wdvx/DlXU1OT2LVrl1i0aJGIjo4WixYtErt27RJ1dXVi2bJlIiUlRcto\noFJbWyuuvvpqUVVV5TVyuLa2ViQmJora2lohhHE0em1traitrfV6HH8iqN2jkEMZlRzKaPPulLXu\nisT2J0pcf498be9JLlevXi1qa2vFvHnzXDIuqBkT9FkN9P3hfjw168e8efPEyJEjRVxcnEhNTfWa\nQaOr987X/u7ZQbzd3yeffFIkJCSI3bt3B9UWlVDJWlfHLP31JSYmiuTkZJGSkiLi4+PFoEGDREpK\nirjnnntEU1OTaGxsFBs3bhRpaWli0aJFYsyYMSIpKUlUVVWJ1atXB5y5Qt2+pKREREdHi5KSEr8y\nHDQ2NoqUlBRx1VVXidraWr/PaXStaWlpmuxlZGSIe+65p9syV/QWMouCRHKZorcIhdLaZrPZfC7h\n+TrXvn37KC8vx+FwIISgoqKCnTt38q1vfYvXXnsNk8nE5MmTsdvtfPDBBwghaGlpYcSIEQwaNIio\nqCicTqffSdq9WfvAczYGb+4X/uTa7IrVJFwChLozMNHX0r27Jczb9t6eAZvNRk1Njbaf1WrtVP3O\nvT/cjzdx4kQtEC0mJgabzYbZbObcuXOdrMBd8ZP3tb/+HO7ZQfTbuJcsLi0tpaWlhYqKCkaPHt3r\nFr+ujln69lssFhYuXMg//vEPfvvb3zJ8+HB++MMf8vLLL/PCCy/wxhtv0NraSmtrK0VFRZpStHTp\nUn7wgx9w6NAhWlpaAP+fbbvdzltvvaUazvxu8/e+9z1tRcHfZ8v9WleuXEl7e7t236Kioli8eHHA\n1SB7i+5YCZMKrkTSjwhk8g8EtTLYlClTsFgshsfzdS518qqvr+dXv/oVAwYM4Bvf+AavvvqqVthB\nVRauu+46bVKBrxLeX3fddZ2Wew8dOsSmTZuwWCy0tLRo/rnqx5fCrygKTz/9NBMmTPA6oQVbAc3f\n+xtOAULd7WMcqALtaXsjhVlVbpuamjCZTEycOBG73Y7dbteq3wFakRL1/+rxVLl2Op0MHjyY3/zm\nN3z44YcUFRVx9dVXc/fdd/Pyyy93SlPWVT959zRmRvLmLTuI3qXnqaeeYuvWrQwdOpSoqCjefvtt\nfvjDHzJ79mweeughv+55d+DrBcdfJchqtZKXl8ff//53tmzZQnt7Ox0dHVRUVGCz2Thx4gSPP/44\nR44c4YknnkAIwalTp0hISMBsNrN582a2bt1KXFwcAIWFhdjtdhYsWODx/qhlzw8fPszQoUNZv359\np0Ij7qjP/YQJE3jjjTdoaWnBYrEEpORZrVbmz59PVlYWNpsNp9NJVFQU7e3tmEymPj+WqHTHy71U\ncCWSfk5XrG1GipeaL/bUqVPk5uaydOlSLaett3Op31mtVgYNGsS5c+d46623MJlMDB8+nObmZhIS\nEsjLy+Ouu+5CCGFoydEfW51Ujhw5wujRoztNRP4o/E1NTaxZs4YXXnjBa67dUObadKe7g7fCDX2/\n+aPU+FK49XKpt2La7XZqamqoqanRgsn05XHhklWusLAQk8nk4k+pll6NiYlh27ZtNDc3M3r0aF59\n9VXOnTvXKU1ZV/3k3dOY6X3VvZ3DPTuD1Wpl+PDhAERGRhIREcGAAQP87JnQ4qlvPY0j/ipBVquV\n2NhYKioqiImJISYmhpaWFqKiohg2bBjvvfceBw8eZNq0aQwfPpx58+bxm9/8BrPZzIoVK1yCF1es\nWMGcOXMoKyvzmHbOZnMtew4wZ84crey5Ppht3759XivXQWDPvbvsX3fddSxevDhsSjt358u9VHAl\nvUYwBSasViuJiYnd0Jr+S1esbd4G4JMnT7J9+3ZmzpzZScE1wmaz8eCDD/L3v/+d8+fPI4Rg4MCB\nnD9/HrvdzvDhwykuLu6U49bpdHLgwAFuvPHGTtZb/aTicDg065m3/KdqG/WlhAcPHkx6ejoZGRls\n3brVUHlwH3CzsrI0BRm6ZiG/XApEBENXLDt6Bcr9ReX1119n4cKFTJw4kYMHD2r5btVE/KNHj+bf\n//3ftUIjasqnDz74gN///vckJSVhMplISkri0Ucf5U9/+hPvvfeeoexA8G4z6nXYbDba29uJjIyk\npaWFL774opN7gr/ZQWbPnk1MTAxRUVEsX76cBx98ULu+nsRT37qPI8EoQfpn6le/+hVtbW3k5eXx\n6quvan2kKAojRoxg3LhxfP3rX+fw4cMu96yurg6HwwFcKmeuXyGCr9xK3MueHz58mCeffJJf/vKX\nTJgwQUvlNXLkSK8uL1197q1WK0VFRdq9WrFiBQUFBRw9epTs7Oygjgndm3WjO1/upYIr6QWagQiX\nKHd/MZuj+eCDxn6p5PZ2dShfkdnqADxw4EBOnTrF/v37AbR/hw0bxoEDBzy232az8f7777Nq1SoO\nHz7MwoULefTRR4mMjOTBBx/kjjvu6KTc6i1l06dP72S91S/HfvTRR1RUVKAoSidXBT3q5FleXu4S\nhVxdXc0777zDhQsXvCqr7talrljI9ccMlTtJfyEUlh1/lOOMjAxmzZqFzWbj6aefZuLEiWRkZPDM\nM8+QkZHRafvf//73PPXUU4waNYovvviCp59+GoBRo0YBxn3nKXOCvwqOuxLw+eef8/jjj3PmzBmP\n/uPeZDIlJYXHHnuMuro6nnvuOTIzM3tU3rpSVAH8U4L0xxo4cCAzZszglltu4Y9//KNLH6WkpNDU\n1MSxY8c6jTF1dXWcOXNGq8Toya1E349LliwhLS0Nu93OtddeS1NTE/X19VoMQ1tbm5YiUe/yAr6f\ne39XM9zHUFVG58+fH/RKXnfFBnTny71UcCW9wCngIoEXpGjE4cjFZrP1WwW3twKMvFlS3BWvFStW\nsH37du274uJiiouL+fa3v01zc3OnY7hPZocPH+b48eNcvHiR48ePExsbi8Vi4ezZsxw6dEg7r7rf\nuHHj2LFjR6dJUD8wPvDAAwwePJiYmBgGDhzo1wSYk5NDeno6DQ0NrFq1CkVRuPPOO4mMjERRFI/3\nysjtIVRLf6FQlvsLXbHseFOg9C4KVquVrVu38tJLLzFt2jQcDgd79+7Fbrfz8ccfs3nzZoYMGUJZ\nWRnr168nJyeHpKQkRo8ezcSJE9m0aRPz5s1j3LhxPPLII50UJFUhSU9Pd6m0F6ifvF5Wi4qKGDVq\nFD//+c9JT0/XAjL115qamurXi/LYsWN59NFHDVOJdSddLaoQiBKk+qiq1Qz1z5e7NX7cuHFa0Kjq\nx6vm0/bmVqK2JT4+nvPnz/P5559zxRVXsHPnTmpqajh9+rQWLxAVFcXSpUuJi4vzWrnOiEDmCEVR\nmDZtmuaXW1FRwQ033NDJiODrfN0dG9CdL/dSwZX0IoEWpOif9GaAkb/n1g/AavnJ/fv3U1xczJw5\nc/j617+O0+nkxRdf9Bi5DZf8GRcuXIgQAkVRWLVqFSaTiSuuuIKqqirq6up46KGHmDt3rl85UdU2\nDhkyhG9+85tcuHCB9957z68J0Gq1UlFRwXPPPUdLSwsRERHs2LEDs9lMfHy85nbRk4RSWQ53uqLU\neJMdT76wp06d4o033qC+vp6TJ08yfPhwLly4wGeffcZtt93G6NGjNb9cgD/+8Y+cP3+e/fv3Exsb\na6ggHTp0iOLiYvLz8wH/ni/obKlTn6OysjLN13fDhg1s2LCB1NRU3n//fa/BZ57oLXkLtG/d75d7\nCW5vlk31Go22Ua3xo0eP1vxvwXiMAe9uJTNnzqSlpYVTp07R1tZGVFQUf/7zn3E6nYwfP553332X\njo4OIiMjmTdvHtnZ2dqLha9+0AfTOp1Ov+aIffv2aeWAHQ4Hzc3NFBQUkJeX57cltydjA7rl5d5X\nHrHL4YPMgxsm+4V//lyjfJGhzlcbCF05965du0R0dLS4//77tbyLiYmJWh5G9Rj6fI0ZGRmipKRE\nlJSUiDFjxoirrrpK/OxnPxNXX321GDhwoFiyZImora31K8epSmtrq1i2bJlITU0VY8aMMcz/6YnV\nq1eL1NRUERcXJwYNGqTlkly9enXgN7OP0d05l3uKYPLG+iM7RjmjMzIyxJgxY8TAgQOF2WwWN910\nk4iMjNRy4TY2Nop58+aJ6OhokZSUJIYMGSLMZrOIjo4WiYmJLnl29du65yj19XwZXXNra6th7l41\nv7R6Dk/PSXcSrKwF2rdqXmL3fMX+HEe/jdqX+jy4aWlpYuPGjR7HGF+5l1evXq3lRU5OTtb6ferU\nqSIlJUVER0eLMWPGiEGDBomEhISAxph169aJtLQ0ER0dLdLS0vwap9VxUd8WVQaDySvsbQzuSWQe\nXIkkjAi1D1Igvry+8oR6O05ycjLf//73ueeee/j5z3+uBe3oA3LA1cpgMpnIzMzEbrcjhODixYvs\n2LEDm81GREQEW7ZsYfv27cyePZu8vDxqampIT08HOlttAN5++23+8z//k6ysLDo6Orhw4QI33HAD\nR44c6WTdMLoedQlSbXtvBdtIPBOsZUcvO97y6aruLnoXgCuvvJKOjg5Onz4NwMmTJ7WUcLNmzaKm\npob8/HzWr1/PnDlzACgrKyMrK4tZs2ZRV1dHbm4uDoeDoUOHcuHCBY4cOcK9995LQUGBx2sxyrX8\n4osvEhMTw/z585kwYQIWi4X6+nqX57S9vd2wVHFfr7IXTN/qS/H6k4vaaJVKzZJhMpkwm83s3LmT\nI0eOcPToUfLy8rRzffDBByxfvpylS5d2sgK7B/JZrVbNnWHJkiUkJCRQXFxMcnIyJ0+epLy8nN27\nd5OSksKZM2e49tprKS8v9xqzoGZecA+mzc/P1zI0eLu38+fP54YbbqCgoECzUAebV1h/rWGDLw24\nKx9gKPCz7jyHH234NvC/wFHgD8Awg22kBTcs9uufFlyVUFWHCuY4RvsEWlHHVwUf1QqiWjoSExNF\nQkKCGDhwoDCZTCIyMtLFgqqev7a21tBqI4QQ999/v1AURURFRYno6Gjtk5iY6LOCVFNTk1bVyL0S\nWn+gv1hwg8FddvyxOOmtZHFxccJkMglFUTrJpZEV0b16mPszsWTJEpGWliZqa2td5M6oDfqVlLS0\nNGE2m8VVV11lWF1Nv71+BUWV/e6qOOdOd8qap+vNzMwUiYmJnazn7pZNo1WqjIwMsWzZMs0yuXHj\nRrFs2bJOfaKuUu3atUsI0dkKbCRbjY2N2vGbmpq0baqqqkRUVJRISEgQaWlpoqSkRJMJI9RzLVu2\nzEUeVCtuIFbYZcuWiYyMjKDlIJQVFrtKr1pwFUWJBO4AcoEpwABgXajP42dbrgC2Ad8VQryjKMpa\n4LfA7N5oj0Tija76IOkDJpxOp2HtdX/OHWyEsxq04ynBud4XTrV0FBYWsnjxYg4fPszatWuZM2eO\nls5GPe+hQ4cYOXIkhw4d0q5r8uTJCCGIiIhg4MCB3Hjjjbz//vtERkbyyCOPuFg3PF3Pe++9p6U5\ny8rK6pVgG0nX0VvV1L/VPm5padHy2/pCteKWl5eza9cuhg4dyunTp1EURUuaD19l9qioqGDmzJko\nisLJkyddqoepgUgqMTExTJ8+nWHDhvHhhx92Sq+nb4NaDGXlypVMnjyZzz//nAEDBvDKK69gt9uZ\nPXt2p5Rn9fX1LF26lOXLl5OVleWSAg/6fuEQb+gDq7zlolYzYKhjnorar5s2baK2ttYljZtq+c3K\nyupkuf3www+1DDF79uzh448/xul0At4D+VTLaXZ2Nr///e/Ztm0bgwcPZtu2bVy8eBGbzYYQgief\nfBK73a4VqdFb3fUynJSUxOOPP65d47333tvpGtX75Cmn8Pz58xkxYkTQfR+usQEhU3AVRZkIzAKm\nc8ly+0+gENgYqnMEwa1AoxDinS//fhaoRSq4kj5IVwcRfcAEwMaNG6mpqaGgoCCgYBN9+iwIXYSz\n0fKeyWTi5ptv5r333gPgn//8J1FRUVrZSoDFixfT2tpKXFwcQ4cOZePGjVRVVfHFF19gMpmIiIjg\nr3/9K+fPn+eKK64gMzOTgwcPahOAe6DEkiVLOH/+PGPGjAG+SnOWnZ0ddpN/sPT1petA0CtA/uaV\nNUJVMPbu3cvZs2e5+uqrGTRoEJ9++ikA3/ve97TzqZX9KisrtRLU8FX1sNbWVgBNcdm6dStOp5PW\n1lZiY2OBS0rTa6+9xj333MM3v/lNlzZs27aNI0eO8NFHHxEREQHAsmXLuHjxIjExMTz22GMu26vL\n9FbrpbRTnp7hmTNnEhsbGxb9bvRiqo4r6vihz0XtdDr585//zODBg4mPjycvL89FadSXZdYvsxsZ\nFZYvX65lihFC8Oyzz3Lx4kUsFgujR4/2KlfqC1B9fT0VFRWcO3eOBx54gNOnTxMREaFlj1EL3NTW\n1lJfX68dy328Ki4uBmDatGmYTCYKCgoM3QS8ZVgIVwW1q3RJwVUUZQyXlNp7gK8Bx7ik0C4AZggh\n/rvLLewaycBh3d8fAVcoijJICPFFL7VJIgkp6kSQlJREYmIiEyZMYM+ePQwfPpz8/HzS09MDqkfu\nraStkc+YrwhnfTvLy8tJT0/XfMtmzpyJ3W6no6MDq9XKG2+8wU033URJSQmHDh1i6dKl3HfffWze\nvJk777yTHTt2kJCQwIwZMxgyZAgff/wx69evZ+7cubS1tXHllVcCeE2mbrVaeeedd/j0009RFEVL\nc/b9739fK9Pa3+mNlHShVqqNFKBRo0Zx0003kZaWFnR1uVtvvZV3332X2267jZKSEq688kqeeuop\nkpKSmDdvHqmpqbS3t2vnTE9Pp6SkRKt6pU8lpf/uhRde4Pnnn9dS0JWXl9Pe3s7Ro0fZuXOnSxvu\nuusu2trasFgsrFu3jgsXLnDbbbexf/9+kpKSaGpqQlEUdu3axYQJE7TnW70f2dnZhs+w3W7ngQce\n6JVUhIHiKxOGfsXJbrczefJk/vznP7NlyxYGDhyoFXsxKsus3i8jxc9ms/H//t//Y/369Rw4cICi\noiKGDRvGz3/+c6xWKy+++GKn4gnuqwilpaVUVFTQ3NzM8OHDtT6Pjo4mOjqaixcvMmPGDP785z93\nKgzibfw1ssL2VBaecHwpDlrBVRTlbWA8l5Tal4H/+tINwAQ8GKL2dZWLwAW3v/X/SiRhj34iOHfu\nHJWVlbS3txMfH6+lEgq09KNRYEFdXR1PPPEE6enphgEs7lZgdRJ1H4AbGhooKysjPT2d2NhY5s2b\nh9PpJDo6mubmZpYuXUpeXh4jRozgxIkTCCG4cOECL730Eq2trVxzzTW89tprAEyYMEELVnv44YcR\nQhgO9HqLh5qmTE1zVlBQwKRJk0hOTu5iT/R9ejslnT9Ktb8TqZEC5HA4OHPmDM899xwQeFCMzWbj\nT3/6E8eOHdNSR913330kJSXR0tKC3W7XAnaMEv+7n1Nf5e43v/kNH374IXv27KG8vJwpU6Zw4MAB\nvvOd73QqSpKSksJTTz1FU1MTxcXF2O126urqiI2NdbHoPf/881qJaYvFwtKlS7FYLMyfP9/ledcr\n3Pp29WWXBW8rQ+5jTWlpKQ6Hg3PnzmljRnFxMYmJiezZsweTyYTJZKK+vt7FWmqEzWZjx44dlJSU\n8Pnnn3Px4iV1YfTo0VitVs0Vq7i4mOnTp2v76FcRqquriYyMZNCgQTQ3N2OxWLBYLERGRjJw4EB+\n9KMfceedd1JTU9NJRr0Fdrm7tKjVId9///1uL83bm3nag6UrFtwM4DMuBW69onMDEF1uVej4BLhd\n93cS0CKEOG+08S9+8QuGDBni8t2MGTOYMWNGtzVQ0n/ZsmULW7Zscfnuk08+Cfl59BNBYWEh8+bN\n43/+5384ePBglzIyqJOI6s/X0NCAzWajoaEBi8WC3W7vNODpI5zVf7dt28bzzz/P4MGDASgqKqK5\nuZlNmzYxa9YsbrvtNl5++WX+9a9/ERsbi6IoVFVVMXjwYDo6OqioqCA6OpoLFy4wePBg2tra+PWv\nf01qaiqnTp3i6NGjvPnmm8TFxbFjxw6t/YWFhdjtdhYsWMBDDz2kXc/48eO19hYXFzNp0iSmTJni\ncu3haK3wh57Ma6kSqFKtn0gBKioqALQlZxV3uVezGaxfvx6bzca0adMMC3Z46lubzaYtK5vNZmw2\nm2aRe+CBB4BLLgdqXtGOjg7WrFnj8ny5L3frfdutVispKSm89tprtLe3c+DAAYYMGcKLL77Iiy++\nqPWBe/vy8/Npa2vTrNJqFgabzYbFYtGue+3atURGRrJy5UqysrJczl9XV+fi9uNuDe2Lsu5vBH9O\nTg7Hjx9n7dq1fPbZZ0RGRhIREcEf/vAHrrzySn76058ybtw4nxlq3OV006ZN7N27l4EDB3LmzBlW\nrVoFXFJ0Vd9doywO6enpPPnkk/zud7/j//7v/4iIiCA2NpaBAwdy+vRpOjo6iI+PZ+zYscycOZNt\n27YRGxvbSb79iclQq0OuXLmS9vb2kJXm9XZfwuHlSMNXFJqnD3AF8BPgL1yykn4KFHMpa8EF/Ihw\n6+4Pl3yBTwLf+PLvtcCTBtvJLAphsV//zqLQVfQRvqGMnl69erVLbsekpCQxZswY8eMf/7hTHkij\nnLqPPPKISEtLE3fffbdhTtDVq1eLqqoqYbFYhNlsFnfffbdIS0sTY8aMEWazWYwaNUpER0eLefPm\niV27dmnRwO45Gjdu3Ch27dol1q5dKxITE8WTTz5pGKWsRgTX1dV5jGbvqejz7sRI1nojr6W/uZaN\n2rZr1y6RmprqNbdxY2OjuPrqq0VCQoImU97yhHrKMespZ6ia0UPfrqqqKnH11VcHlXWjrq5O3HHH\nHWLt2rWGfeBJ9oyi6vW5e4cNGyYSEhIMc7l66/dQyHpPZVHQ/63PUKBmKRg1apQYNWqUSE5OFiUl\nJVpObX+u0SiDxZgxY8R3vvMdER0dLRYtWiTuv/9+lzy0RlkcMjIyxP333y9GjBghFEURkydPFk8+\n+aRL7mJ9X+uzbwRyD4yelYyMDLFr166Qjl29mafdiB7JoiCE+Bx4HnheUZRruJQ1IRe4/8uT/0xR\nlGeFEAeCPUdXEUKcUhRlBrBZUZTBwFvAI73VHomkO3F/4++ukq9tbW2cOXOG119/nfj4eJcAlsrK\nSm1JUW9peuONN8jIyODdd9/lJz/5CS+99JKLb9l///d/qy+bjBkzhv/4j//gf//3f1m/fj233XYb\nf/nLX5g6dSrjx4/XqvAYBWM4HA4cDgctLS2cPXsWs9lMS0uLyxKwaiGsrKzs5HMb1tYKP+iNvJb+\nBiHq+9PpdLJo0SLOnTuHw+Hgiiuu4PXXX8dut3fKCmK1WrnnnnvYsWMHc+bMYcOGDYbnMOpbdelf\nPb/ZbCYhIYHm5mYSEhLIy8vrZFlTfVkHDBgQ1P345je/yc6dO2lqauJ3v/sdBw4c4MYbb9Ta5En2\n1Oc7Ozub6dOna/dz4sSJvPnmm0RGRnLq1ClWrVqF2Wx2scob9bveZ9fofH0Fdz/ZQ4cO8cQTTzB4\n8GCX8se33HILhw4dYsuWLQwYMICbb77ZZzCZHnc5Vd0Njh49CsDOnTsxmUxMnz5dswjrszio1nXV\nReGzzz5jwIAB/POf/2TdunV0dHRoz5vNZqOuro6Ghgba2tpoa2vjlVde0aqbGfnZ6lfLPLnnfO1r\nX/OaEzgYQp2nvScJSRYFIcRHwBPAE4qijOdS4NldwBxFUf4hhBgXivME2bY9QFpvnV8i6SncJ4JQ\nLTmrxRBeeeUV/vM//5Of/exnWmCLeyCPftA7evSo5i8IsHXrVtrb27Hb7cBXk6wakHH+/HkGDx7M\n7373Oz7//HOGDh0KXMpy0N7eTmNjI7fffnunFEl6hfrIkSMsX74cRVHYvHkzMTExFBYWYjKZmDlz\nppaeDIwngN5Ywu8N/Fn+DOW5/F1qVvtzwYIFfPHFF5w5cwZFUWhra2PhwoVYrVYeffRRrS9UpXXC\nhAm88cYbAJw9e5a6ujpuvPFGl/N689ndunWrYZL+rKws7RhWq1ULimxpaSEuLq7Ty1Og90V1D5g+\nfbrPDBCeIuGnTp3KHXfcofmUT5061aNPub7fw03W1b7et28fJ06c4M0338ThcFBfXw98lQ5LzVJh\ntNzvDfc+nDVrFgUFBVoKtkceeUSTB316MTWLA1wa8/bs2cPJkyeJiIigo6ODzz77jKFDhzJp0iSX\nceaJJ57AZrNx8eJF2tvbWbZsGcOHD+8k30Yleo2CCNXiFeqYG6r+7I2X4lAR8jy4Qoi/AX9TFOUX\nXPJ/zQ31OSQSSc+hDnDXXHMNAF//+tddFEWjIAkjS5MaLawoCsnJydokq1rOrrrqKi3q+Ec/+hGp\nqamsWrWKxYsXuyga7u0CcDgc/OlPf+KNN97g4sWLDBs2DIfDwfHjx7nvvvsoKChg9+7d5OZ+NRwZ\npU4KZ2tFIPgz4XfXOT3dS31/WiwWfv3rX/PZZ59RVFQEwIMPPtipepO7krZ+/XrOnDlDVVUV9913\nn98+uy0tLVgsFuLj4zGZTOTl5XWSOavVSmxsrOaPC8ZKhD/+26qyNm7cOHbs2OExG4M32VPvZ2Nj\nI1VVVTgcDuCSpXHv3r3MnTu3U1CSvt/DTdYrKip44YUXaGlpob29nY0bNxIREcHixYsZMWKE1gcP\nPfRQl86j3iO9JTUuLk5TZlX0sqwf82655RYaGhpYtWoVJ06c4OGHH2bKlCkux8vJyWHUqFG89dZb\nPP/889jtdnJzc/n2t7/N9ddfr51DVViPHDlCYmIiCxYsMAwiTE1N5cYbb3QZb0Pdnz35UhwyfPkw\nXPgDzkIAACAASURBVA4fpA9umOwnfXB7A33d9sTERM3HT+8D5w1P/m+tra1i9erVora2Vmzfvl3z\n8921a1dAvoGtra0iKytLmM1mYTabxcCBA0VERISIjIwUQ4YM0fwkPfkhGlVI668+uOGA3t/Ql4+i\nvk8zMjJESUmJKCkpMfR3VGlsbBSJiYkuvpTqZ/Xq1V5l2h8fZn+q4nnzawxU9jw9n/76Vfd1H1wV\nNRYgKSlJmM1mMWLECGE2m8WPf/zjbvUjD6aKV2Njo0hJSRFXXXWVRzlQK+ep41ZKSopITEwUq1ev\n1s5bW1srSkpKRHJysuZfXFVV1ckfWd+2/jB2eaNXK5lJJJKeoyei/SsqKlizZg0Wi4W4uDhtCczf\npS9Pb/5qsvwpU6ZgsVgMLWf+WAysVisVFRVa5aGioiKGDx/OL3/5S86dO6dZ/NyX2nylTgo7a0U/\nwd26PHv2bO17o23V7+12O2VlZYYpvNwr6i1YsIAJEyYYWku99bmRDO3evRuA7373uwghOmUbMTqm\nL+tpILKnP76RpdGf/cNB1lVXqddff52FCxcyZ84ctm/fzty5c7t1yTyY1Q7VneXgwYMMGzbMcBt9\n5bzXX3+dH//4x1RWVmr5e/UVIhVF4cSJEyiKwv79+/m3f/s3j23ztz/7a6YYPVLBlUjCmJ7ITThh\nwgReeOEFrwE83nAfhNXl2fr6elpbW6mvr2fs2LGdAnoCmVhSUlK05dg1a9bwwx/+kB//+McelSJf\nqZMCXXKWdA9Wq9WvJWer1cpPfvITl3RanuRUf0xPbjb+nE+VjxdeeAG49KK0a9cuzVWgqKiIsrIy\nZs+e3eka9Eqp0+nUAs30Cm6gBKuo9oa7SjCo98xut2O1Wpk4cSKjRo3q1vLawT77VquV6dOns2PH\nDi141mgb9Zh/+9vfiI2NxWw2c+jQIfbu3cutt95KZWUlxcXFbNiwgSuuuIJhw4Z1qnxmdFx/+jMc\n89oGilRwJZIwpCei/dVztLS0YDabgUu+rvHx8V2ymKiWCYfDQWtrK4sWLWL48OFadgT3NgQywSQn\nJ5OTk8P999/v03fRZrNpvsS+Sgz394kg3FEVitzcXC3/pyelVS9TiqJofuGBkp6eTkNDg6bQHjp0\niLa2toDbrQ8064p8hYui2lXGjh3Lo48+yvjx47n99tt976DD23hi9Fswz36gY3NdXR1nzpxh/fr1\nmEwmVq1axZEjRwB47LHHmDVrFjU1NeTn5wdlYOhq+8KZiN5ugEQiCZzq6mpyc3M1q+OKFSvIzc2l\nurq6285RVlbGp59+ypNPPqlFEfuLOlHYbDays7N5/PHHmTp1KhcvXqStrc1FMfG0nz+kpKRQWVnZ\nKbjGCKv1UoWz+Ph4WltbNcVdP7m5p21qamoK+NolwWHU956+0/eTtyIP7scQ4lLlO09WNk9UV1dz\n9913s3DhQpqbm2lubua1117Dbrdry8cPPvggL730Enl5eR7boQaamUwmQ/kKVP69XWt/x59r9baN\n/jd/n32j4wU6Nufl5bFnzx4eeughzp49y6hRo0hMTNRKMg8bNoyCggIyMzOBr17cglVGQzV3hINs\nSQuuRBKG9EQEtPs58vPzWbNmDYcOHdJquevxZR0pLy8nPT2dZ599lr///e+cP3+eixcvcubMGYqL\nizl37hzz588HLvn9qj6S0PNWhp4sgSkxxmazUVpayvHjxzXrvpFFzSgfMsCIESNcXnT0rjEtLS28\n8sorxMbGuqRfcpcvTzKt+k82NDRoWR7uvvtuXn75Zb7zne/Q0NBAZmam15UOf9J0dXX1INTlkXsL\nffs8XZO3a/VmtVR/1/+mptzy9ewbyag/Y7P7/bZarWzbto2PPvqIjz76iOTk5E6xDjabTXNB6Up/\nhWruCIeVLangSiRhiPtE3B25CfU+b6dOneK1117D6XQihDBMum804LlPLA0NDdrk/5e//AUhBJGR\nkQBUVVURGxvLlClTWLNmDS+88ILmGhGIcunv4K93wYiLi9N83+666y6EEJ1KYPb1NEr9Bb3MOJ1O\nKioqGDt2LElJSYYvPNnZ2Rw/fpykpCSvvrd615iWlhYee+wxTCYTcXFxXhUYo0lcfTYsFgtr167l\nwoULjBgxgpiYGMxmMz/5yU88BhepeFM0urqMHOj+/igrvakEq4rkyJEjaW9vB766JkVRNEu8/nv9\ntXp7mQAoLS3FbrdjsVhYsWIFTqeTnJwckpKSWLp0KcuXL3cJfjWS0RtuuIHk5GT27dtHTk6ONh4b\njc3u99tmszF+/HjuvPNO3n77bRwOB/n5+S5p8fQuKE1NTUErl12dO8LJxUEquBJJGKJONtnZ2d0e\nAV1XV4fNZuPw4cMMHDiQiIgIFi5cyLBhw8jOzmbp0qUeJxh9JLDT6aSoqIjm5maGDh3KgAEDiIiI\nICIigqioKAAtcb7FYnHJU6rm0PV3cletxd4mZPdJb9WqVRw+fJjW1lZuuukmTCYT7e3tREVF4XQ6\nwyrBeThTXV1NaWkpTqcTh8NBc3MzBQUFREZGMnz48E4ZEiZPnkx1dTWTJk3y2k/Z2dmMHDmS/fv3\n88wzzxAbG8sPf/hD/vrXv3ZSiv2dxK1WK+np6bz99tuaD+XTTz+N3W4nNja2k6uMkeVORd/u8vLy\nLhVh8LeIQyDKSm9Y7PTts9vtFBQUYDKZOHv2rFbARV9oAYyv1ZfVcuTIkRQUFOB0Ol3Gmvr6emw2\nG5GRkdTU1JCTkwN4ltHbb7+d/fv3a/fIfWz2dL93796tBbzGxMRw5MgRysrKKCgo0LIqqPsbFX4I\nRrkMNigxnAqESAVXIglD9JNNdw4qNtulKlGLFi2itLSUjo4OIiMjmT9/Ptdccw1PPfUUv//979mx\nY4e2j37AUyeW4uJiNm7cSEJCAqNHj+bMmTNER0czbtw4/vGPf/Dggw9y8uRJqqureeONNzCZTGzY\nsEGrNKUvcVleXu7RDcLdWlxWVkZ6errhIK62rb6+nlWrVjF16lQqKip49dVXefPNNzVFyul0ct11\n1/U560R/JScnh+PHj1NRUaGVzFWt/BMnTqS+vp4lS5Zoad5UK9qrr77KHXfc4dH3dt++fZSWlmqB\nYG1tbezevRun09kpcNK9bLCnBPtWq5XnnntOk7sVK1YwZ84cysrKXBQTFSMl0UjR6OoycjDlkcGz\nm0RvWez07bNYLDidTj7//HMtOPXmm292seB6ulZPLxPqtbW3t2M2m3E4HERFRaEoivab1Wrlo48+\norKyUhtLsrOz2blzJ++//z4nTpxg+PDhKIrCq6++ysWLF2lqaiI1NbXTOOXpfuvLnBcWFnLvvfcy\na9asThki9IUfRo8e3SXlMtigxHAqECIVXIkkjOjpyUY/IF9xxRV8+OGHCCH49NNPSU1NxWQykZSU\nxOOPP47NZly612q1eowEPnLkiMtSnHslnvj4eOrq6vyKavZkLd60aZNhPlK979uRI0fYuXMncXFx\nmlWmo6ODNWvW+JUfVRI6rNZLJVdvuOEGCgoKMJvNrFixgtTUVOx2O/X19aSmplJTU+NiRTtx4gSv\nvfYacXFxhhk5VMX5xRdfRAhBQkICZrNZK+2rV0j1k/iSJUuIjIxk5cqVZGVlGbZXdeVRMyqYzWaX\nMr7Q2c9Tv69RLtOuLCP7u78/ykpvWuzcq8/l5+dz/Phxnn76aW2bK6+80u975f4yob82k8lER0cH\nixcv5rrrrtNenAYPHsz69etdxhK73c7HH3/MokWL+M1vfsO5c+cYMGAAMTExXnMwe7vfaptMJhMF\nBQWGbg3p6enk5+dTVFRk6MbQE/SEe1yokAquRBJG9PRk4z7B3H333fzrX//izTffpK6uDvgqqGfa\ntGmA8YA3duxYCgoKSE9PZ8OGDS6RwI8++qjmy2s0cE6YMMEwqhlcB1tP1mJfeSPvuusuAM2Hs7Cw\nkKioKBYvXhz04N3Xg3b6OlarlaysLPLy8qiurnaxuKkKipGl12w2U11drZVudT+mJ8XZvY/Uv6Oi\nonA4HJjNZtrb27WIcaPVg6effprTp09rrgrufp7BPLfBLiP7u78/ykpvWuz07VMLeah+0+vXr2fD\nhg3aPfTnXrm/TLj7b6svtKpV2H0sqampoaamhsmTJ2MymRg0aBC33347e/fu5emnn/bpr+/rfnu7\nBv3YbzabPbox9BRdlc0ewVeps8vhgyzVGyb7yVK9/pQKDfR47qUefZV/9NQGf0r3qsf2tq3R+b2V\nNnWntrZWpKWliZKSkoDukfs16tsQaLnOvlAuM1xL9erxdd9bW1vFrl27RHJyskhLS/Orr1tbW8Wy\nZctERkaG1/5Zt26dyMjIEImJiSIjI8NrOV+1pPD9998vNm7c2EnuvD23wZSC9XZtwRzLn/28yXR3\ny5p7We9gxz71OKtXr3YpB75r1y7Da3MfS+bNmyfS0tJc5CEjI0Pcc889WmldX2Wa1XYY3W9v/eBe\nlnrevHmitra220oU91UCKdXb68plX/hIBVcquD1FqCaCUClQRscx+q6rNc/d9/d3ItDv769ir56r\ntrY2oHvkbXLx91pD/QLSFfqDgusP3hTWYBQJ/TZGfamXK/02aWlpIjk5WZSVlXVqizeZDOXLUHe+\nWHm7Zz0pa125RvVFJCUlRezatUvr27Vr14qpU6eKuro6l+3d+622ttbr8x3ouBbMtfWFl2eVUL6c\n+UsgCq50UZBIwpCuLg8Z+fLa7XYAj7lng615rp5PzWxgs9loaGjQ/jXyjzW63kD97PTL2fp2eHId\nMLrGQH2ewynCuL+guh6MGDHC78h/XwE2ejlR5UwNatM/HwcOHGDbtm0AWjT9r3/9a6677jqXYDe1\nHSUlJS65TEPlT98TvvnBBiWFGk/ZCby5BKnZB9TKc6dPn/7/7L19fFTVnfj/vjAJA0QwMiGggEGW\nEhrAVmxaXU2+XdHdxsrXX9oVwRDrEz9EG5AusD8NLghSyxaFoAGyiBoiVGoHhRprgbXEbtIG6VZ0\nmyDLg/hAQi4EDOiYTDi/P8K93pncebjzlJnJeb9eecHM3Idz7znncz7ncz7n82H27NkMGDAAu93O\nunXrOHr0KNdeey3f+973ut1LkyXGsIjguVmtsbFRDzlo9L8OVj4GW3/x5BoQ77FwpYIrkSQg4Q42\nZopYS0sLABkZGfp34Fs5C6YM3oK7oqKCP/7xj3o83SeeeILnnnuOBx54gPnz5wcstxXhbhyctE0p\n1113naV4n1YV1kTaYZxMeLfFSMSR1dqJls53165d3aKFuN1urrrqKv72t795+AF//PHH7N27lyFD\nhniU49ChQxw+fJjy8nLS0tL00FDa9SC0yVCwUR+SAWO/1iKqBFK0nE4nTz75pO5DLYTg3Llz9O/f\nnwsXLnD33XezZ88ePXuY2YZU7+gZZpvV3G43ra2teggzLZJMIH98K3ImHiYaiRILVyq4EkkvxEwR\nM1qoIqWceQvuXbt2cerUKdLS0hBCcPbsWQYPHmx6rplVJhThrg1+nZ2derzdYON9WlVYjddzu90c\nOHCAG264IWpCX25mMydUS7rZwJ2amspf//pXrrjiCtauXdutfyiKwl/+8hc9Vq+2cU1RlG7Z8Fau\nXMnhw4e57LLLePXVVykoKIjIZMhK1IdkwV/yB+9+bZZ5bt68efzhD3/A6XRSXV3N4MGDu2UP84W3\nHNLe/2uvvca//du/8eCDD3L77bfrlvpAk2pvOVNSUsKxY8dM05cbn7+n+n6irFQllIKrKEoKMFEI\n8ZeeLotEksj4W/LXBolIhH/xFtwrVqwgJSWFffv2UV5eTmZmJnPnzmXy5Ml6zEkNK8tfZsLeuCx5\n+vRpPv/8c1auXMnAgQM9LCz+4n1qCoe/rERmaLv8nU4nd9xxR1QV3HheIuwpQrWke1tCS0tLcblc\nfPHFF/zmN78hPz9fnwga28Lp06dJSUnxmNSoqqpnw1NVlRUrVpCXl8fnn39O37599Yx+ZtezitWo\nD4mMWfIHu93uNzyXJu/S09NZv369bnlXFIXa2loKCgrYs2cPCxcu9MhYFkxZtIQ70BVb2e12c/78\neVpbW2ltbQ0q3biZxbisrIw77rjD7717qu8nykpVQii4iqIMA/4DuAE4AXzT8NulwCYgF2gFfiaE\n+P3F3+4EngT6AHuB2UIIV2xLL5HEL2ZL/tqSrOZD6MtSEIwFwVtw5+bmUlNTQ3V1NUIIBgwYwIsv\nvugR7ieU5S8zYW9clhRCoCiKPtjcd999lJSUeFzPn1WisLDQkr+xqqpMmjSJHTt2RGX5LlGWCHsK\nKz7bRowD99y5c+nTpw82m41+/frp2ap+9KMfMXXqVKqrq/VwUocOHaJPnz5MnDhRTy3cv39/PRve\nvn37OHLkCB999BF9+vQBYNGiRTgcDubOnevhlxuqVU7LrtXR0UFaWlrcWtXCxSz5g1ncaiNGRfTe\ne++ltraWRx99FJvNxuWXX86ePXs4evQox44do7i4OOiyaHLn8OHDvPHGG3z++ecoisJLL73Epk2b\n6NOnjz6BCaY+FEVh6tSp+sTErF9HMptZqITav2JNQii4QAewClgDlHn99jRwQggxQlGU7wK/UxTl\nCuBy4Fngu8AR4HVgAbAsZqWWRIWGhgbL5zgcDkaNGhWF0iQ2Zkv+QnRlBRJdEUZ8WgqsWBCMirS2\nXLh582Zqa2u7zf69Fc0lS5bQ2trK3Llzu/np+lP0vJclOzs7GT9+PIcOHWLmzJmW4n0G62/sdDo5\nd+5cxHwrfZEoS4Q9jdUNOcaBOz09nRtvvJE333yTkydP6v61b7zxBldccQV/+9vfaG5uZs+ePZw/\nf55Tp07x7rvv0tzczNy5cz3SCrtcLr7//e/z/e9/n40bNwJw//3309rayq233qqn9G1sbAzZKpco\nVrVg8Kfoez9nMHGrjbJq/vz5FBcXe2SfW7hwIceOHdNjYgcqh7fcOXnyJF999RWdnZ263Lzkkku4\n+eab6ezspLa2Nqh043v37vWZFVLr15HMZhYu8bThzYyEUHCFEKeAPyiKYuaQ8mPgWxeP+7OiKAeB\nKcA3gDeFEIcBFEVZR5c1Vyq4CcsJoA9FRUWWz7TbB3DwYINUcv3gLbTr6+s5cuRIN2uCMTWm8Xt/\nFgSzTRrp6el6VipjGt78/HyPAcxf6tNAyrBxWfKrr77i6NGjpikwzcpv1Sph3CkfKd9KXySTMhNN\nrExMvH2958yZQ35+Pj/4wQ/0ZfCFCxfy5Zdf8sQTT3D69GlSU1N54IEHeOWVV/jwww/p6Ojgiiuu\noG/fvrhcLlwuF1OnTtXbnKqqVFVVATBp0iQef/xx7rnnnohY5BPFqhYM/ibPZs+p1ZeZ5dbfez1w\n4AAul4tjx475PN+sHN5yZ9++fQBcddVVNDU18U//9E/cfvvtKIrCggUL9HIGqo9A/TpesplpxMOG\nN38khILrC0VRMoEBwDHD18eBK4AxdFluNT66+L0kYTkDXACqgPEWzmvA5SpCVdWEUHB7avOAt9Be\nvHix7hebkZGhWwqys7P1gQKsWw+Ny4XG2b9xMNHSsvpKfaqd4z0gmCnDiqJw6623cvLkSf77v/+b\nSZMm+fVNtGqV8B5Em5ubSU9Pj4hvpS+SSZnpabyVGO/+N2TIEIqLi9m2bRs1NTX8/ve/R1VVFEXh\nueee44svvuCSSy4hNTWVlJQUmpqa+M53vsPs2bNZunQpNTU1Hu4wd9xxB+fPn/eYOB44cACn06lv\nRgvHKhfvVjV/WFl+Nz6nL0XL30pHXl4eTqeT73//+9185QMpxt5yJy8vj5qaGk6cOIHNZuM///M/\nqa2t1TOeXX/99bS2tnrsM/A1sfLXr+Mtm1m8E5cKrqIoo4HfX/wogEk+fGcvAEIIccHru07Dv97f\n++SRRx7ptqN7+vTpTJ8+3doDSKLMeLpyc8Q3W7duZevWrR7fffLJJwHP66nNA95Ce9myZfqAX1ZW\n5rFrXLPghmI9ND6f5nNrloZ3165dtLW1maY+1QYzbUDwpwzv3buXPXv2APjdiKJh1SrhaxCdMWNG\n1BWNRFZmehpfSkxra6tH/9Osgx9++CHV1dW0traiKAodHR2cP3+ewYMHc9NNN1FbW8uDDz7I888/\nz6effgrAP/zDP1BbW+uhIA0bNoyKigq9TWrhxgoLC5k0aVLYFvl4t6r5w8ryezDP6S9aTH19PW63\nm7S0NNxuN/X19fp1A7kAeSuiM2fOpKSkhPr6ehYvXsyNN97Ivn37qK2txWazUV9f3y1deCArtVm/\n9k6dfvfdd/tckZLEqYIrhDgKBKwxIUSLoigdiqKMFEJ8fPHrK+my6A7xuob2vU+eeeYZrrkm/hUn\nSWJgNjl6+eWXfbpY9PTGIbMNYUZrrS8rYSDrodFia+baUF1dzZYtW7rFkJwxYwZvvfWWqSLtbf2o\nq6vzqQxHezk/kO9uNElkZaanMXNvcbvd5OXlAd373+rVq/WoHCtXruTkyZMsWLCAgoICoGtvwJVX\nXsnNN9/Mzp07efTRR2lvb2fQoEEecWn9tRfNqhspi3wihZELtPweyrOYWURramqoqKigpaVFn7xD\n14pVRkZGN5mxZMkSrr/+elNFUut/xgQQ2jUWLVpkWscHDx7klVdeISsrCzCX8776tfEYm81GSUmJ\nXLnxQ1wquH5QLv4ZcQIlwIKLm8yGA3voUmb/qCjKKOBTYA7wUuyKKpFYI1obh6wODN7WA1/WhGCt\nh5qloqmpyTRQ/tixY1m7di379+9n0aJFLFiwgClTpvhdrvPejFNcXOzT7zXY5fxQlQHpLhC/WNms\ndP3111NTU6Nb3fxZ7drb27n00kspKCjguuuuQ1VVJkyYwC9+8QtsNhtDhgzh/PnzfPbZZ3R0dDBo\n0CA9Lm2g9mIlWkeg9ppIYeQCLb+HswHPKKu0eq+vr2flypXcdttt7Ny50yNEmLGO3G53NzcT47s3\nSwDhL+PZggUL2L17N1dddRV2uz0kOR9I9ibSxCaaJISCqyjKSOA/ATuQoSjKh0CNEOJ+YB7woqIo\nH9HlpDlNCNEJfKgoyr8Au4F+wA66Qo3FPcePH9dn8lYIJbqAJH6IlqXR6iDnbT3wZ02wEjQ/KyuL\nJ554wsPlITU1lYULF+ppgv2VR7Nw+bJyG5UEMyUzmEEhHGVAugvEH1Y2K2nLzMH0P5vNxl133aVb\n9DQLr6qquuJUUFDAa6+9hsvlQlEUve0a7+3dXqxY5P09W0+vBoWCr+X3yy67zNSFycqzmMk06FKk\nb7zxRnbt2qWvWGmoqkprayt5eXnd3Ex8vXtfslM7p76+nvfff58rrrjCVLEOlmBkb6JMbKJJQii4\nF90PTF0WhBAq8EMfv1UClVEsWsQ5fvw448aNx+X6oqeLIokxkbYERnKQC8Ui4G2R1pYCp06ditvt\nJjU1lfb2dtra2igpKcFms5Gens7GjRs94uIahXlFRUVA3zhfSqavQSFS70m6C0SGSFifrNRpIKub\n9zWbm5sZNmyYbrk1XtfhcLBt2zaOHj3Kq6++SmtrK52dnbS1tXksgXu360g/WyKGkfO1/B6oz4dz\nv1mzZjFmzJhuMkNVVY8sdJpF3+grDYFlhXYPVe3KulZZWamHnHv11Vf59NNPLcfe9UciTmyiSUIo\nuL0JVVUvKrdWIwUAVAOLI18oSUwJxRJophREcpALxSLgyyKtKAoffvihHmjdGKy9b9++fuNF5ufn\n09TURFZWlsfGt0C+a/5IRGUgmYmE9clKnfqzuhnL5J1219c1tViqQ4YMYd26dWFZ6gI9m9vt9vDv\n1cqRyGHkvN9/tJ7FWO9aHGINVf06C117e7t+Xy3aheZqFayscDqdOJ1O7HY7w4cP58SJEwwdOpQp\nU6Zwyy23UFFRERF3AisxxHsDUsGNW0KJFCBdFJKBUJQ0M6UgEgNDOBYBfxZpbTnXSrB26EpCsWPH\nDp544olu1/RV/kDWwERWBuKNcKyvkbQ+hVOnZv3Pl8Jjds1x48bx+OOP09jYyAsvvOBzCTxUjM9W\nWlpKSkqK7t9rfIZE9Qs3m3DE6lmMbVDLQpeamorb7SYzM5O0tDTWrVtHc3OzpXblXWfDhw+nrKyM\n3NzciLoTBBM2sTchFVyJJIEJpBSEOzBEwrrpy9fQu2wOh3mwduj+nKqqMnXqVD2dsC+CGTwSWRmI\nN8IZrCNpSY9UnfpTeAJd098SeDho10lNTcXlcmG322lvbzeN7ZxMfuGxeBazNuh2u5kwYQIAW7Zs\noaCggPT0dCD4duXtflFcXMyYMWMi7k6gnRtMDPHegFRwJZIEJhilIJyBIRLWTX8WaWPZ/B3ny593\n2LBh3ZYXITRrYDIpA7EmEtbXaFjSw61TfwpPMCsYvpbAw8XpdFJeXk5HRwdpaWk+JwPJ5Bcei2fx\nFze3ubkZ6GrbmZmZzJgxw3K70ibxhYWFUXWN8hc2MVnaQ1AIIXr9H12+AGL//v2ip9m/f78ABOwX\nICz+VYV4brKf1/VO46F+q6qqIlqWlpYW0dDQILZv3y4mT54stm/fLhoaGkRLS0vA8zZs2BDwOI2G\nhgYxefJk0dDQEIliW8bqc27YsEFMnjy529+GDRtiXPKeI9JtzR+RfN893daMhNq/olEOY3+Nl3Jp\nxLKtRRozWWhsg9GSJdGsw3hrH5Hkax2Ja0QA3U5acCWSBCbUpdhQQ4f1lHXT6nNKv9rYEsn33dNt\nzbss8eC+4t1f46VcyYCZLDS2wWhucotWHcr20YVUcCWSJCBYpSDUpeR4WeoM9jmlgI8tkXzf8dLW\njPSU0h2Mj328TAYSjUDv1ixuLkRelkSzDnt7+5AKrkSSBASrFCR6SCyryk9vF/CxJlnfd08p3YH6\nazxOBhIFq7IwWm07mnXY29tHn54ugEQiiR2FhYVUVVVRWloKQGlpKVVVVRQWFlq+lra0F0rW5Koy\ntQAAIABJREFUvXAJ9t7JqnDFK/HwvoNpGz3Zdq0Qyf4q8UR7tyUlJbS0tFBSUuL33WruCk6nM+7b\njaQLqeBKJL0Ih8PhscSm/T8UhSQUJSFSikWiKCiS2JNMCq7WXzMzM2lpaSEzM1P6kkcI7d06HF1p\ndI2ffSHlV2IhFVyJpBcSjqVN81sz+q41NjYGpVAcOnTIkmD3HghCubck8QlWaQ3UNiLRfqRyEr9Y\nqRutLWjKrfGzr2MjJXci3YZkmzRH+uBKJL2QcHyzQvHj3bdvH0uXLuWnP/0pEPzmNu8dzonuQyzp\nwmrGs2CifgTTNiLRfiKZeSqYe6mqSnNzMxkZGb02YH+wWKkbY1vIyMjQY2ubtYVIyZ1IZuvzvm6s\n2mQsCCcjohGp4EokSUakhIMvrITN0QR6ZWUlTU1NlJeXM2jQIJYsWYLNZvM5QPgaCPLz82X4ryQg\n2AHZikIQTLsMJ+RTOMpJqH1STuiCI5S6sdIWgjk2mDqOdH1GS2HuaSKlsEsFVyJJMqIxm/cW3sGG\nzamsrGTTpk2cP3+e1NRUOjo6OHz4MHfeeSeLFi0KeyCQ4b8SC6sDshWFIJh2GU44M39l0TYf+VJu\nQu2TMp5zcISiOFppC4GOVVWV8vJynE6n3zqOdH0m2wQo0gq7VHAlkiQhmrP5QMHQA9G3b1/69OlD\nSkoKAEOHDg0rUYOve0fbei0JD6sDcigKgb92qbWP/Px8yz7o/sriS4ENt0/KeM7BEY7iaCWGeHV1\ndbcUvaqqUl9fT2VlJXa73W8dR7o+k20CFGmFXSq4EkmSEI3ZvJVg6MZzNCWzuLiYgoICdu/ezaJF\ni5gzZw7t7e1MmzbN730DDQT+7p1MvmjJhtUBORSFwJ9/ubF9WO0TZmUxbk6C7v0jUn0yluHXEnGS\nGI7iGOx+BFVV2bJlC1VVVfq9NMttZWUlJ06cYPjw4ZSWlmKz2ZgzZ45f6/GsWbNQFIWKioqQ33Wy\nTYAirbBLBVciSRKiMZsPZYA2KhHa/VtbW3E4HOTn53PdddcFfX8r1pVk9EVLNkIdkMNV8CLZPoxl\nCdQ/ItUnw9kUapVEniRGYyLgr+04nU6cTid2u53hw4frSm5xcbHfWMVaORsbGyPyrmM5AYomkVbY\nE0LBVRTFBqwECoB+wAfAPUIIVVGUS4FNQC7QCvxMCPH7i+fdCTxJVzi0vcBsIYQrVuU+fvy45bAd\nDQ0NUSqNJJR363A4GDVqVBRKE3miMZsPZUOZ2UAwduxYHnvsMcaOHWvp/sEO7Mnmi5bsWB2Qw1Xw\nItk+jGUJxpUmUSxsyTBJjMZEIJDvtVb/paWlDB8+nLKyMnJzc/2+s0i/61hOgGJBpBT2hFBwgf7A\ne3Qpr0JRlJeAx4ES4BnghBBihKIo3wV+pyjKFcDlwLPAd4EjwOvAAmBZLAp8/Phxxo0bj8v1RSxu\nJ/HLCaAPRUVFls+02wdw8GBDwii5ENnZvJUBOpASEU0BHKldzpLYEOsBOVq+isH2j2D8gnu6XcpJ\nojn+2o6x/m02G8XFxQGVW4iPdx0v7c6MSMmHhFBwhRBtwEuGr+qBv7/4/x8B37p43J8VRTkITAG+\nAbwphDgMoCjKOrqsuTFRcFVVvajcVgHjLZxZDSyOTqF6LWeAC1iviwZcriJUVU1IBTca1/QnCHty\nw0MwikYiL71KwiPaltRA/SNYv+CebJfJtmEpUgTTdhwOB3PmzAlaWYyHdx0v7S6aJISCa0RRlBTg\nbmCxoiiZwADgmOGQ48AVwBi6LLcaH138PsaMB66xcLx0UYgeVutCohGM0hwPy7FmikYyLL1KIkO0\nfBVDmVTGW7uMh/4bz/hrO1brvyffdby1u2gSlwquoiijgd9f/CiASUIIl6IofYBKYJcQ4i1FUTIA\nIYS4YDj9AtBp+Nf7e4lEEkV6csOD2UATD8uBkvggnnwV47VdJsuGpUjTUytjkSZe2100iEsFVwhx\nFPDYjaIoSirwK+CgEOKxi8e1KIrSoSjKSCHExxcPvZIui+4Qr2to3/vkkUceYfDgwR7fTZ8+nenT\np4f+MJJey9atW9m6davHd5988kkPlSZ2xJMSAfGxHCiReBOv7TLe+m8y0xPvOl7bXTSISwXXG0VR\nBtC1Sex3QohVXj876dpstuDiJrPhwB66lNk/KooyCvgUmIOnH283nnnmGa65Ri5hSyKD2eTo5Zdf\nDmmzWzwTz5sVQC69SkIj2u1atsvkIt7loEZvand9eroAQTIPuAH4fxVFOaQoyoeKoqw0/DZeUZSP\ngApgmhCiUwjxIfAvwG66fHGPA//RA2WXSJIabbOC1ZB4sUYuvUqsEKt2LdtlcpAoclCjN7S7hLDg\nCiFWACt8/KYCP/TxWyVdPrsSiSTCJNpmBbn0KgmGWLdr2S4Tm0STgxq9od0lhIIrkUjij960WUHS\ne5DtWmIF2V7iF6ngSiSSkOhNmxUgcXzsJOGRn59PU1MTWVlZlJWVJX27loRHIDko5UbPkSg+uBKJ\nJM5wOBweGxS0/yerEE80HztJaAgh2LFjh96Ok71dS8IjkByUcqPnkBZciUQSFsm+WSFRfewk1vCu\nZ1VVmTp1Koqi9HDJJImAtxyUcqPnkQquRCIJi2TfrCB97HoH3vVcVlYGwLBhwxg3blxPFUuSIHjL\nQSk3eh6p4EokEokfepuvcW9F1rMkksj21PNIBVcikUj80JsCo/dmZD1LIolsTz2P3GQmkUgkQZDs\nvsaSLmQ9SyKJbE89h7TgSiQSSRAku6+xpAtZz5JIIttTzyEV3CDYt28fX3zxhaVzPvzwwyiVRiKR\nSCQSiUTiD6ngBmDnzp1MnTq1p4shkSQNMvC5JFmRbbv3Ies8fpE+uAE4ceIEoAAfWvz7154orkQS\n98jA55JkRbbt3oes8/hFWnCDQgHGWjwnIxoFkUgSFhn4XJKsyLbd+5B1Hv9IBVciCUBDQ4PlcxwO\nB6NGjYpCaRIXGfhckqzItt37kHUe/0gFVyLxyQmgD0VFRZbPtNsHcPBgg1RyDcjA55JkRbbt3oes\n8/hHKrgSiU/OABeAKmC8hfMacLmKUFVVKrgGZOBzSbIi23bvQ9Z5/CMVXIkkIOOBa3q6EEmDDHwu\nSVZk2+59yDqPX6SCK5FIYooMfC5JVmTb7n3IOo9fZJgwiUQikUgkEklSIS24XQwFeP3117vtmP/L\nX/4CXEBR+lu6oBAdF/+3EbjcwpnvhXheOOfK8yJ73mcAVFdXd2tPb7zxBgBbtmwJKTqDRBIssq1J\nYoVsa5JYcfDgQe2/QwMdqwgholuaBEBRlGeBh3q6HBKJRCKRSCSSgDwnhHjY3wHSgtvFb4GHqqqq\nGD/eym55icQar732GsuWLUO2NUm0kW1NEitkW5PEioaGBi10528DHSsV3C5OAowfP55rrpG75SXR\nQ1u+k21NEm1kW5PECtnWJD3AyUAHyE1mEolEIpFIJJKkQiq4SYyqqlRUVKCqak8XRSKRSHoVUv72\nPmSdxxdSwU1iZGeTSCSSnkHK396HrPP4QvrgJiGqqqKqKo2NjQD6v96pBSUSiUQSWaT87X3IOo9P\npIKbhDidTioqKvTPy5cvB2DWrFky44pEIpFEESl/ex+yzuMTqeAmIYWFheTl5dHY2Mjy5cspLS0l\nOztbziQlEokkykj52/uQdR6fSAU3CfFeFsnOziY7O7sHSySRSCS9Ayl/ex+yzuMTucksiXE4HMya\nNUvOIiUSiSTGSPnb+5B1Hl9IC24So3U2iUQikcQWKX97H7LO4wtpwZVIJBKJRCKRJBVSwZVIJBKJ\nRCKRJBVSwZUkFDKQtkQiiWekjOp9yDqPT6SCK0kopCCRSCTxjJRRvQ9Z5/GJ3GQmiQmqquJ0Oiks\nLAxph6nMFCORSOKZgwcP8sorr5CVlQVIGdUbiNS4FO74KDFHKriSmKDNcPPy8kLqwDJTjEQiiWde\neeUVfvGLXzB69GjsdruUUb2ASI1L4Y6PEnMSSsFVFOVRoAjoB3wC3At8DKwD/hE4B6wQQlRePP4f\ngGeBAcB7wD1CiNM9UPReS6RmuDJTjEQiiUc0GZeVlcXo0aO57bbb2LlzJwsXLiQ3N1fKqCQm3HFJ\nrkxGl4RScIEzwEQhRKeiKMuA1cA+IAMYCYwG9iuKshdoBbYBtwoh/qwoyrPAL+lSiiUxIlIzXJkp\nJnk4fvx4SL5qDoeDUaNGRaFEEknoGGWc3W5n586dHD16lGPHjlFcXNzDpZNEk3DHJbkyGV0SSsEV\nQpQbPv4JmAL8MzBPCCGAI4qivAX8X+AzoEEI8eeLxz8H1CIV3JgSacurzBST2Bw/fpxx48bjcn1h\n+Vy7fQAHDzZIJVcSV3jLuIULF3Ls2DGmTZvW00WTxIhQxyW5MhldEkrB9eIB4EXgGeCI4fvjwBVA\nf6/vPwIGKYrSXwjxZawK2duJtOVVZopJbFRVvajcVgHjLZzZgMtVhKqqUsGVxBXeMi43N1dabnsZ\noY5LcmUyuiSkgqsoyi+Bc0KIDYqiPA10Gn6+YPjz/t74bzceeeQRBg8e7PHd9OnTmT59ekTK3Zvp\njZbXrVu3snXrVo/vPvnkkx4qTbwxHrimpwshkUSM3ijjJJFBtp3okHAKrqIoa4F0YObFrz4GrqTL\ncsvF/78NtAE/MJyaBTQLIb7yde1nnnmGa66Rg2406I2WV7PJ0csvv0xRUVEPlUgikUSL3ijjJJFB\ntp3okDCJHhRF6asoymagUwhRdNHnFuA3wE+VLsYA+XRtLnsT+JaiKN+6eNzDwEsxL7hEIpFIJBKJ\nJKYkkgV3GjCdro1ktwICeBe4D9gAHAVcwCwhxBkARVGmAy8rinIJ8F/Awp4ouEQikUgkEokkdiSM\ngiuE2AJs8fGzqUe/EOItICdqhZJIJBKJRCKRxB0J46IgkUgkEolEIpEEg1RwJRKJRCKRSCRJhVRw\nkxgtv3UoWaMkEolEEhxS1kpijWxzgZEKbhJj1gHiuVPEc9kkEonEiFFeHTp0iCeffJJDhw71dLF6\nNVbHkEQecxK57LFCKrhJiKqqNDY20tjYCKD/X1XVuO4UxrLFczklEkliEwn5oqoq5eXl1NfXs3//\nflRVZf/+/bqslcSeRFNwQ7m/v/Fd4knCRFGQBI/T6aSiokL/vHz5ctxuN4WFhUyaNAlA7xzeqQJ7\nAk2hNXbY1NRUysvLycvL6/HySSSS5EJTLEKRL0Z5derUKWbPng2AEILVq1ezfv167r33XubPnx+N\noktMMBtDwPf4ZvX4aBFKOzQb3wFmzZolk0V4IRXcJENVVc6dO8fatWtpbm5m+fLllJaWcuDAAZxO\nJzt27ADiq1MYO6zb7aa0tBSXy0VHR0dcKeISiSSxiYRiY5RXQghUVeXCBZ8Z4P2Wxel0UlhYKGVb\nmFhV+oI9Plp1FE47LCwsJC8vj8bGRn18z87Olm3IBKngJhmqqrJlyxYKCgpIT08HIDs7mxtuuIE7\n7rgjLjuFscPOnTuXlJQU7HY7aWlpcaWISySSxCYS1i+jvFqyZAn/+q//SlNTE08//TTz5s1jypQp\nQcnVcKzIEk+sKn3BHh+tOgqnHXorwdnZ2WRnZ0esbMmEVHCTBLMZYWZmJjNmzNA7RE93Cl+zYWPZ\n0tPTWbFiBe3t7WEr4tJCIpFIjETC+mWUVzabjSlTptDa2srmzZuZPHky2dnZumJkJntisTze22Sf\n1fEt0PHh1JHx3QOm9RCpdjhr1qxeUb+hIhXcJMHfjNBbmeypThFoNuxwOJgzZw65ubm6w3w4iri0\nkEgkEiORnOgbZanD4eCxxx5j7NixgH/ZEwsfyt4q+6yOb76OD6eOjO8eMK2HSLRDrewS30gFN0kI\ndkbYE50i2Nmwd9lCVcTjZQOBRCKJTyIx0TeTV2Y73LVjtXtF04eyt8s+q+Obr+NDqSPju3e73eze\nvRvo2lcSaMzrDXXTE0gFN0mIBxcEX4QyGw5HEZe7TCUSiT+iNdEPRvZEU1ZL2RcZQqkj47tvbW1l\n0aJF+rV81YO0wkYXqeAmGfE4I9Rmw/X19SxevJhly5aRm5sbtTLKXaYSiaQnsCJ7QpXV/vxrpeyL\nLIqikJ2djaIoAY/13ny4YMECADZu3CjroYeQCm6SEY8zQm02fOTIEVRVxeFwRNW6HM/WbIlEkrxY\nkT2hymp//rVS9kUWIQSNjY0IIQIea7b5EODFF1+U9dBDyExmEaCns6HEO5pfkqbcGj9Hk3i0Zksk\nkvgmEvI8GrLHSgYrKfvCI5xsYd6bD2fMmEF1dbXUD3oAqeBGgERRcHuqnE6nk6KiIsrKysjIyKCs\nrIyioiKcTmdU7yuFvEQisUogORmMHI2G7NHkqObPuXz5cp9yVMq+8LDyrr3xVnALCgrYsmVLUONu\nougSiYJUcMMg0XJCB9N5otHBCgsLqaqqorS0FIDS0lKqqqr0OIGxLItEIklOwpUXwcpzK/eJpAwL\nVY5KrBOJdx2KfqCqKuXl5ZSXl0d13OstY6tUcMMgnFleLLHS0aLR8DWfW80HSft/MAGzI1mWWHXq\n3iI8JBJ/xLofhGt5DSTPQ1VYIvUOQpWjyYDV9xjue4/Eu7aiHxjbltvtprKykvr6+qj1nd4yRiXc\nJjNFUfoA1woh6nu6LImyYzWY0DGxiJ8Y7LKZv7JozxNKhp5YBT/vrUHWJRIjkegHwWTkClZ2BSpP\nIHluJQRXNOVpb3Q/sNqWIiWDw3nX+fn5NDU1kZWVRVlZmV/9wOl0Ul5ejtvtxuVyceLECUpKSigu\nLmbOnDkRq+veFic5YRRcRVH6AZuB/wOkAQMufp8KrAP+ETgHrBBCVF787R+AZy8e+x5wjxDidKTK\nlCg7VgMJblVVmTdvHh988AE2W1eT8KUEh5P+Mdhdw/4Gkry8PMuCK1adurcJD4nEjEj2g0OHDvHk\nk08yceJEn+cGUjytJJrxlucOh0OXeVYMGtGMRxuPkXKihdW2FGkZHM67Pn36NM8//zxPPfUU4F8/\nKCwspKmpicrKSk6cOMHw4cOx2+04nU6GDRtmOoEKZSzubXGSE0bBBQTwIvA48BfD9/8fkAGMBEYD\n+xVF2Qu0AtuAW4UQf1YU5Vngl8C9kS5YPM+ojR3Be7nFeMwHH3zAihUraG9v9ym8Y2WZNBtIMjMz\nAUISXJHo1MEIlN4mPCQSMyLV31RVZf/+/fq/6enppv09kpZX8JTnRpnnLQ8DKSxmZVIUhYqKipCN\nBMb3E46xIVHwV3eFhYXd3kE8yGDvtvvRRx8xdepUv7F0HY6uNPXXXnstJSUl2O12li9f7nMCFYpF\n2+l0kp+fnxCrzpEiYRRcIUQ7UK0oypVeP/0zMFd0Bao7oijKW8D/BT4DGoQQf7543HNALVFUcOMR\n745gVMSNs12bzUZ7ezupqam43W4P4R2JWbEVgWxmSampqQlZcEXClSQYgZIoLisSSTSJRD+orKxk\n06ZNuFwuAFavXs369eu59957mT9/vsexgVbSrJbH4XBQWFjoV+YFMmj4KlNjY2NEjASRMjbEu6Ls\nr+7M3oEv40hdXZ0epjLaeLfdjRs3YrfbSUtLY9y4cT7Pczgc5ObmUlxcjNPpNJ1AhToWe0/UNOJ1\n1TlSJIyC64cxwBHD5+PAFUB/r+8/AgYpitJfCPFlDMsXNfwJJ7OOkJ2d3W22W15eTmtrK+np6Sxf\nvhy3282ECRM8rhcpi0ywAtk429QGklAHzWAs2IHOD1agJIrLikQSTWLdD8zkRbjlMZN5mmxcvHgx\nAKdOnQqoHGrKsKIo3TaomZUtmGeN5BJ8vO8X8OU24u8deB8PsGXLFgoKCvRzvevNqqIfrYmBZskd\nNmxYRFxfzNpLa2sru3btYsaMGXFZ55EkGRTcC0Cn1+cLPr43/tuNRx55hMGDB3t8N336dKZPnx6Z\nkkYYf8IpmI5QWFjIiBEjKCkpwe12s2TJEl2AGK9nVblUVZXKykoAbr31Vj0bDAQnkI3P5Z23WyPY\nQdOfBTsYQlHutfvU1NSwcOFCj98++eSToO8tkSQy4bhuFRcXU1BQwO7du1m0aBHz5s1jypQpAZdr\n/U24rZTHbINQamoqjz76KIcPH6aiooJLLrkkoH+wds+KioqILJ1Hagk+0fYLGOsumHfgcHQlWGht\nbaW5uRn4+hlbW1u7jZuR3MRmpe36e1YzrI7F2rtyu920trayZMkS3G43bW1tvPXWW1FZgY0nkkHB\n/Ri4ki7LLRf//zbQBvzAcFwW0CyE+MrXhZ555hmuueaaKBUzcgQjnILZWKaqKu3t7djtds6fP8+e\nPXsYP3686azWyrKGqqps2rQJgObmZn71q1+Rnp6OzWYLe+dxsIOU8Vput5uysjJmzpxpuYOGYjk2\nCijvZ3z55ZcpKioK+v4SSaISjuuW1udbW1txOBxMnjw57OVaK+URQrBjxw6eeOIJ3G43qampqKqK\n2+3mrbfe4uzZs2zfvp0TJ07w6quvsmvXLm655RYOHDhAfn4+e/fu9ZA1kXJfitR14sFX1Qpa3amq\nSlNTEzfddBM5OTk+oxM4HA7S0tL46U9/qn+nKXd5eXnA19ZMoJsS7KsN+WpziqJ41HmgthsKoaxG\nau1l9+7dLFy4kJkzZzJs2DA2btxoaVIT75Z+XySigqtc/NP4DfBTRVH+CFwF5AMPXvztOUVRviWE\n+CvwMPBSTEsaJYKdwfqzeBqvofnfPv/882RkZPD4448D3Rt1IOVSVVUOHTrE/v37df+jjo4O+vbt\ny5133smrr77qc/Oa0+nk3LlzbNmyxedzWZlFGp/P7Xbz0ksvUVNTQ0lJiSUBLt0OJJKeY+zYsTz2\n2GOMHTu222/RUNK8FRhVVRk1ahQLFy6kra0NVVVZt24dbrebo0eP0tnZycaNG2lvb+f48eP89a9/\nZcSIEd2UAV9yRJOxWgKBYFweIiGPEnW/gKqqbNu2DeiysoPvd1BYWMjEiRPZvHkztbW1XH/99dTU\n1FBbW6sbW1paWgDIyMgAArchX64ro0aN4vjx4x517q/thvrs4axGdnZ2UllZyaBBgwIam4z3TCRL\nvzcJo+BejH97EOgLpCiK8iFwGCgENgBHARcwSwhx5uI504GXFUW5BPgvYKHZtRMNK8LJV0fQrlFf\nX8/KlSspLi5m586dZGVlUVdXB5jPar07wsGDB1m2bBmLFy9m7969PPnkk6iqihACIQTl5eUIIXjv\nvfdwuVxkZmaaWmIqKipYu3YtBQUF1NfXs3jxYpYtW0Zubm5Iy0iacNu/fz+rV69m+PDhzJ49m4kT\nJ4a02SCc5VaJRBIakVyuDQZvBaasrAy3280dd9xBVlYWK1euJD09nfr6evr160dbWxtCCC5cuMAH\nH3zA2bNneeutt3C5XNTX1+vPYFR0p06dyuLFi1m+fDlCCF2mAX7lm/cEPxx5lEgTd83lbfz48Rw+\nfFg3nhw4cICbbrrJZ3QCzd+2pqYGgJkzZ1JSUmIanae5uTmoNuTd5kpKSvjyyy956qmnGDhwYDeL\nbn5+fthL+8Hsp/GF0UVh6NChDBw4EJfLRUdHB2vWrAnYXxLN0u9Nwii4QogLgK+pULGPc94CcqJW\nqB7CinDyNUBo19i2bRtHjx5l586d2O12ysrKLM1qDx8+zPbt25kxY4aHUvnEE09w9uxZMjMzGTBg\nAO+//z5tbW3U1dVx3XXXAd07bnNzM+np6aSkpOhKqGblsLpBQ/PVWr9+PZ999hmXXnopGzdu5MUX\nXwypc4az3CqRSCJPNJS0QLv27XY748aN491339UVqy+++IILFy6wb98+ANavX4/NZmPx4sVkZGR0\nW1m79tpreeqpp5gyZQqZmZm4XC6WLl3K1VdfjdvtDipRRXZ2dkTkUSJM3FVVZc2aNbjdbs6cOaN/\nv2zZMhwOB2PGjOkWncA7QtD1118PfJ2hDDzbi/bOvaMHeSunxjpxu93s27ePN998k5MnTzJ8+HBK\nS0ux2WwUFhayY8cOU2u+VcJRMs3as+ZLHkx/SVRLv0bCKLiS7kRCOE2bNg3AYzOF2azWO9TKwYMH\nOXz4MO+88w6A/u+YMWOYMmUKzz33HIMHD2bu3Lm8+OKLpnEgvTuu5iP1ne98Rx9QGhsbqa6u9uu6\n4AtN4S4rK+P111/n0UcfteTsL5FI4p9IKmmBlOZZs2YxadIkRo0axdmzZ1m7di233347+/btY8SI\nEXz66afcdttt7Nmzh4ULF3qsQBllZmdnJ0uWLCEtLY2zZ8+ybds2XnvtNYYOHRpyoopQNgLF88Td\n+Nzp6enceeednD9/nqqqKvr27cu8efOYPHlyQPcVm81GfX099fX1evxcY5xjXxE4/K0YOhwOJkyY\nwNtvv43dbmf48OGcOHGCoUOH8sMf/pAhQ4bgcrl45513fFrzg8Xb1cK4GTwQZu3Z4XAEnR0tkSz9\npmhLyb35D7gGEPv37xfJSEtLi9iwYYNoaWnxeUxDQ4OYPHmyaGhoMP3O+/e77rpLDBgwoNvfXXfd\nJVpaWsSqVavEqlWrRG1trcd5xuu0tLSIhoYGsX37djF58mTx4IMPipycHHH11VeLyZMn63+rVq3y\nOG779u36+YGeu6GhQaxdu1YMGDBArF27NqjzoklVVZVI5rYWiP379wtAwH4BwsLf/l793kKht7e1\ncGhsbBR33XWXaGxs9HlMbW2tGDVqlNiyZYvIyckRf/d3fydycnLEG2+80U2WCuEpM/v37y/69esn\nUlJSxIABA8TIkSPF/fffL8aNGydeeuklDzm1YcMGD3mo/W3YsMHj+mYyPFZEo62ZPXdOTo64/PLL\nRU5Ojsdzeo9x3mOLrzHD7J0Fe67xuJycHDFmzBjx8MMPi6uvvlqMGjXKY1wcNWqUaZ0FS0NDg8jJ\nyen23MESjA4QzfMjyddjCNeIALqdtODGiFiF2fAV4y/QMomZFcTh8B1q5eGHH2bGjBlc6fUPAAAg\nAElEQVS88847rFmzhvz8fIqLi7nmmmtwOBx6MHZVVX3GgdRmk9qM0MxHyixsWbCzSKP/kcPhCMtF\nQSKR9B7ExdCGossA0g1VVamrq+O+++7j0ksvJS8vj7fffpshQ4bw+eefm8YYXbx4sS4zy8rK+P73\nv8/f/vY3Tp48SWdnJ3/84x/5+OOPOXbsGMXFX3vdBRsRJ1E3AvnCV9KGXbt2kZaW5tfaGmjM8PfO\ngnUJMN7DZrNRXFzMtGnTeOihh/S9LTfddBO//vWvWbhwoe4vbCWTnZmrRWtrq+V9JGaWeqvJlxJx\nzJQKboyIVZgN432gK5f75s2b/fp2ad95N2CHo3uoFbPOvnr1av73f/+Xb3/72918obTr+osDqS0Z\njR071q9QCnYpsremJZRIko1Yx9/0FRi/rq6O4uJiD6Vyy5Yt+oYxgL59+/Luu+/qm4+8yztu3Dhd\nPpaVlVFcXKy7hr3++uv89Kc/pb29XXcb0wikrCX6RiBf+HpubQ8HdK+v+vp6tm3bxrRp0xg3bpzP\nMSNQCmCrme/mzJnTrY3a7Xa++c1vcubMGRobG5k2bZplPcCfq0W4dZuoob+sIBXcKBOr2bXZfQ4c\nOMDmzZs5fvw4V111VUiCL9CmC0VR+O53v+txb7Nn83cdb+Xal1AKdhbZW9MSSiTJRqwHYTPFx+Vy\n0dbWRkFBgV4mTdZlZWXxs5/9jI8++oiNGzcGFa3lsssuY8KECaSnp5Oens7f//3fs2PHDtLS0pgy\nZQpDhgwxLZsvuZjoG4EC4c+w4V1fK1eu5OjRowA8/vjjPscMYxQh74g9VlcMze6hKApTp07F7XaT\nnp7O66+/zoQJE+jfvz8QvB4QjbpNVou/GVLBjTKRnF37s2aYbdj66quvGDt2LMePH+f8+fM89NBD\nPp3yfeGvsxutsna73e+zeV8nMzOTmpoaPf6j97GhzE79BeGO953CEkkyECmLaywNA8byGhWKJUuW\ncP/99wPogfEPHDiA0+nEZusaOrWoMx0dHZw9e5bRo0fz4osv+nWFuvTSS+ns7KS+vp7S0tKgXah8\nycWE3wgUAH/jgXe4y9tuu00Pd9nY2OizvWjfHzlyxCNij9l9jVb7YNv23r17cTqduN1u+vfvz8cf\nf8zcuXO57LLLTDcS+nv2QHVrtc8lq8XfDKngRplIzsD8WTO87/Ptb3+bP/7xjzQ0NNCnTx9OnjzJ\nmjVrePDBBz3CdFnxwZkxYwbV1dV6pws3y1ewlplgy9mbOq5EEo9EyuJqtS+Hqlj7891sbW1l/fr1\n2O12PTC+2+2msLCQSZMmefiFnjlzhp07d1JbW+tTDnor7VlZWTzxxBOoqsrTTz/N9ddfz8yZM7ns\nssss+WlqBOvClUxo9WUW7hL8txftT1uN9KcQq6pKeXk5Tqcz6DjsTU1NVFZWcuLECS6//HJsNpue\nMleLQRusT66/urXa55Ld4m9EKrhRJhKz62BT2BrvM3ToUPr164cQAkVRuOSSS+jbt2+36wbbMRwO\nBwUFBRQVFVFQUBDSUo6G1rm8nwXMM/kEU05VVTl37hxr164NOmi3RCKJDJG2uFodhK0O8oHK63A4\nmDt3Ltddd103eaIoCq+88gput9tD5o0ePZr6+nqfctAsiQSgL2W//fbbDBs2jJtvvjmkSUKoK1/R\nJhZ+1GbhLv0pkMa6yMjIMFWItTY1ceJEWltbqaysxG63Bx2Hfc6cOVx77bWUlJToK5zeMWgbGxuD\nqmuzug21zyW7xd+IVHBjRDizayvWDO0++fn53HPPPezevZtFixbx+OOP6zFgjR3D7XZTVlbGzJkz\nu23y0tBS8Bo3q3lvvAj22fw9S15enkdnt9KBtU0fBQUFpKenA1/H/IvlJhVJdGloaLB8jsPhYNSo\nUVEojUQj0qsnwQ7CoQ7ylZWVrFmzhvT0dNO0pQ7H15FgvJMA1NXVsW7dOiZNmuSRRSuQHDTLgvU/\n//M/fOMb3yAvL49du3bpaX8DbQpOJCLtR22mMI8bN47HH39cH9MOHDjADTfc4PPegfaWaG3K5XIx\nd+5cPvvsM06fPs3ll1+uJ3OYM2dOQPeC3NxciouLcTqdHjFozaIKaecE+44CteFA9AqLf6A4Yr3h\njx6Ig2slrpyVuHze19RiNdbW1urfGeML5uTkiAEDBoicnByfMfqWLl0qBg8eLOx2u8jJydHPGzVq\nlN+YfGblMXuW2tpaUVtb2+35Vq1apZdTiy149dVXe5TT1/VWrVql/9ZTsSHN6O2xSUOPg/tbAX20\n+IeW/uz2AeKjjz7q6UePObFsa8HKqFCu609O+osR60v+bNiwQVRXV4ucnBzx85//XIwaNapb7Fnj\n8VpM78bGRj2utt1uFyNHjhRvvPGG32c0K4Mmk9544w0xYsQIkZmZKbKzs0VGRobo06eP6Nevnxg+\nfLgeDzzU2KmxxKytBdMmQomvajamGa+3dOlSPR5xMHFwr776arF06VLTuMPDhw8XiqKIfv36iSFD\nhojU1FQxcuRIcdttt/mNkexdJu9nNN7D19gWzHvIyckRa9eujWifi3dkHNwEwKp7QLDWDO9rjh07\nlscee8xjY5kxpe7q1av97vxVVZUBAwbwxRdfMGTIEM6fP8/tt99OWloav/rVr/y6GJiVx+xZampq\nTK0/M2bMoKqqisbGRkpLS0lJSWHFihXk5ubqx/qyHM2YMaPX7BTtHZwBLgBVwHgL5zXgchWhqqq0\n4kaRaC17Blp2D2SJ85Y/hw4doqysjNmzZ2O32zl37hwnT54kJSXFp0zdsmULVVVVvPHGG1RUVOip\neU+ePMns2bOZPn06CxYsCNo/Utthr6oqAwcOpLm5mTNnztDW1sYVV1wBQEtLC9/4xjf4+c9/bmlT\ncDwRjFXfyjioWVb379+v/5uenq6fV1lZyXXXXcekSZN4/vnnddcAf9ZNbS+J0+nkjjvu0D9r4+Oq\nVasYMWIE//iP/8jvfvc72trauO+++9i+fbvPGMnemLVhY7v1NbYFeg/Nzc3Y7XYAXC4XmZmZSetq\nECpSwY0x4fiq+VpSCBS70cyNwel0sn79ek6cOOFz5+/Bgwd59tlnefXVV+ns7KSjowNVVfnlL39J\nZmYmGRkZHoJj4sSJPPnkk4wcOZLRo0f7jSVp3LR26623+vW3S01NxeVyYbfbaW9vR1VV/Tl8DXDV\n1dUUFRXpzyw3nCUL4+lacJH0JL78KmO97GmmWBs3DcHX8gdg8+bNHD16lFWrVqEoCuXl5XR2dvL7\n3/+eb3/7292UJWOCG00RPXPmDG63m5SUFFpaWtiyZQtjxozR0+pqMbjFxWQR2vlaeY077N1uN199\n9RV2u53+/fszYMAAHn74YdasWUNzc7OHApdoBOsGAMGNg5WVlWzatAmXywV0xV9fv3499957LwUF\nBaxZs4ZNmzZht9tJT0/H7Xbjcrno6OhgzZo1epKIp59+Wk+koaoqkyZNYseOHR5leP/991m/fj0n\nT55k5MiR/OEPf6C5uZl+/fpx+vRp3G439fX1pjGSg8Hf2Hbq1Cn27t3r063Oe+KwceNG2traqKur\n84gRLJEKbswJx1fNlzUjUOxGs07ind/abBPHsmXLcDqdCCFISUnh9OnT9OnThxEjRvDII4/wwgsv\n6LuIAX1mXVlZyfvvv6+H0pk7d65uBTZuUDNuWvMVr7aiooLy8nI6OjpIS0sz9ZUzllkLP3brrbdS\nUFDQK3aKSiSxxpflLZIbnULJtKRN3r3lYUtLCwDp6emMHj2akydPoqoqffv2JSsri//+7/+mqKiI\nGTNmcO7cOSoqKrj00kt1C5kWQeHuu+8mJSWFf//3f2fo0KEsXLjQI/Si9l6amprYsWOHRxng60QC\nZjvsz5w5w9mzZxkyZAg333wztbW13RS/WCe+CAd/Vn1/iX+ME4VAz9nZ2UlzczONjY2kp6d7hHXz\n3tQFsG3bNgAKCgp8rhxqdaSNjzt27KBPnz7YbDY6OjrYuHEj0JWZ7pJLLvE7zvrD6XSajm1Tp05l\nx44dPq3a3qHstOgbiWrpjyZSwY0x0QjRESh2I3QXNtrn9PR0nzt/jaklV69eTWZmJrNnz+bXv/41\no0ePBrqE1gsvvMCGDRsYNGgQAH/605+w2Wx85zvf4U9/+hNCCH70ox/x29/+1sOa4p3+1yxebbDv\nyziwyiQPEkl0iGWQeKtuXFr/9568L1myRJ+ENzc3s2TJEoqKiti6dSt9+vRBCMH999/PmDFjOHPm\nDIsXLyYtLY3Zs2cDXXJ0yZIlutw5dOgQmzZtYuDAgUyZMoXs7Gz9nZiFADPu6tfek9kO+8zMTJ5+\n+ml+8YtfYLPZsNlsLFmyhNbWVubOncv8+fMTMvuUmVU/mPTD3s9ZXFxMQUGBvnF63rx5nD59GqfT\nyZ49e7DZbLz44ou6cUe7XnFxMUePHuXw4cO69Xf37t2MGTPGZ9QdY3veuXMnJSUlPPfcc9hsNn78\n4x+zfft2fvKTn5CWluZ3nPWH2aZDbRID3bOyGd+ndg+3201NTY1p5jyJVHBjTjR81YzXNIvdCL4t\nxP6WFI2pJVevXs1NN93E6NGjsdvtqKrK1KlTURSFU6dO8fnnn+tZWvr27YvNZqNv376cOnWKtrY2\nfvWrX2G323WBDV3hWSBwVIhg35dZ+DGZ5EEiiRyxiDUdrhKtKQk1NTWAp8zQJtjV1dWkpqbqQfif\nffZZxo4dS0NDAydOnGD48OGsX78et9vNl19+2U3u/Mu//It+L/AfAsy7DNp53jvss7OzWbdunf7s\ny5cv5/7772f9+vWMHz8+7F33PYWZVd+XXPeeKJiFb2ttbcXhcOiW8zvuuMNDUc7MzKSurk4/Xpus\naIojwKJFi3A4HDz22GN6WnuzseXMmTN0dnbidrsZOHAgLpeLrKwszp8/T1VVVdDjrK/3YnwHx44d\n09sNdM/KZkRVVVpbW8nLyzO19Eu6kApuD+HPn9bKEpT38b5iN/q6VjBLimPGjGHSpEn89a9/1TtS\nWVkZLpeLlpYWBg4cSL9+/ZgwYQI1NTVMnz6dlJQUtm3bRr9+/bjssstwu90cPXqUu+++m5kzZwJY\nilcbyLcvUG7xRFnWk0jimVgEibeiRHvLP6NybLPZuP7662ltbdU3z2oycvz48ezcuZOamhruvvtu\nLrnkEt544w3sdjvDhw/Xldwf/ehHZGZmdlv90kKIBXoviqIwbNgw0/ejWXKNvxuVOM3aaLfb9bJq\nlt1gFap4d2nwluvByPH8/Hx947QvRdnoi1pYWMjIkSOprKzkT3/6E3379mXevHkeriXeY4vWjnbu\n3MnZs2fZuHEjNpuN8+fPs3TpUiZPnsyjjz4akZjr2jvIz8/njjvuCCorm/E9hapg9woChVnoDX/0\nQJgwX1gNa+Xr+EiHxzIL+fLDH/5Q9O/fXwwYMEAMGDBA2O12oSiKuOWWW7odv3btWpGTk+MR2iWS\nZfQXkiaeQoXJMGGhhgmrCvG8/b32fUezrUWzT1kJOeZdDn9hw7zPy8nJETk5OR5yYvv27SInJ0eM\nGTMmYAgwMyL1XlatWqWHjtJCSeXk5IgHH3zQUkioWMm+SLW1UOV4oHBjWn3/3d/9nV7n/tDakfbe\nx4wZIwYMGCDuvPNOj3EsGu936dKleuhOX204WmH5EgEZJiwBCXZZLphdutqfP4un1Zm92Uz5scce\nIysriz59+rBx40ZmzZrFhQsXuOuuu7odP3nyZEpKSjwc4QOV0Qpm5dMsOom4rCeRxDOR7Ltm1w7k\nluRLXubn5wf07TSz8DocDv0eNpuN4uJicnNzfW7sinYUCc3fVHsOzQe4tbXVY8+E5qtqlv0xEWVf\nqHLc4XCYrtR51/d3vvMdhg4d6pGgwwxvi3xRURHPP/88V199NYcOHeLQoUPs2rWLW265Jez69m5L\nvrKyebezSLs6JiNSwY0Tgl2WC2aXrtbhAi1dhZMOUjunrq6OO++8E7fbzfe+9z2mT59uevzYsWM9\nlo3MlhYjsZRmLF8s/AUlkt5IMK5NkbqHmTzw7tvem7E0vAd+76Xd+vp66uvrPeSmFkJKw0xWBhtF\nIlS55s9H1fhOfJUj0WVfKHLc+C6g6x2cO3eOLVu2AF31/f777wNdbnfGjVtm9ze+z9bWVtrb26mq\nqqKtrY2f//znHD9+HOjuH+sLX23Buw6NWdnAv/IazYlmMpD0Cq6iKP8APAsMAN4D7hFCnO7ZUnUn\nmF2lxlmsv126/ojEBo7CwkKPa5w9e5b+/fubzop9DYTenToYhTuYwcJ4v1j4C0okkujgT4n27tva\nZixtEu1r4A8kExyOr8MXXnfddT7j6XpHgPElP8ONeuD9HNpnVVWpq6vzSJ9uLEc8y75Iy3GzMS01\nNZXy8nLWrVsXVrhIo3/sPffcw2uvvcbSpUspKiqirq7O1D/W33NbSUUfjPIai4lmIpPUCq6iKIOA\nbcCtQog/K4ryLPBL4N6eLVl3Ai05BLtL19eSla/rhDKz1+L3nTp1ioEDB7J161Y6OjqoqanhW9/6\nlocjfKCls/r6eo4cOaLvcPU3YFgdLOQyjkRiTrxvPgqE1re9N2NpMVF9Dfz+ZIK3bNq8eXO3jV0t\nLS10dnbSt29f0tPT/VoTI+Ei4Os5nE4nZWVlHD16lNGjR+txeidMmMDq1avjWvaFYswIdmx0uVzM\nmTOHfv36ceHCBT1ZhhYmzl8WUH8uJ1p9vvfee7S3t/PWW28xaNAgnn76aWw2m9/x01dbqK6u1q3L\nYH0VVhIYywquoigTgP8DnAReE0K0K4qyCCgBOoAXgCeECDKPXXS5BWgQQvz54ufngFriUME1+tZa\nsTx479INJDwCZZcJZtArLCxkxIgR/OQnP0FVVa644gpGjx5NbW2tvtyXl5dnuqw3b948PvjgAz0J\nxGOPPcbJkycZOnQomZmZPtM5hmt1lss4vZuGhgbL5zgcjqRN75uI8VQ1jHKqrq6OtrY2fZd7sBN2\nTSYoiqIbBLwn/7W1tQBcf/311NfX6yGo3n//fUpLS+nfvz9PPfWUqUUwmi4CqqoyceJEZs+ezerV\nq3G5XMyePZshQ4bwi1/8Qo8YYXzOcFbFIoUVOW7WPoOxys+ZM4fTp08zcuRIBg4c6JG63bu+vQ0v\n5eXlNDU1MW3atG6ZxLT61FLi9u3bV48KFCgGrb908loq+nCt7Ik+YY0WlhRcRVH+H+AV4DyQCixW\nFGU5sIguy2hfYP7F338Z2aKGxBjgiOHzR8AgRVH6CyG+7KEymWLs0FYtD+PGjTONH2iWRtDfdRob\nG/0OelqWsvHjx/Pb3/6WwYMHY7fbmTp1Ktu2bWPFihX6JjIzIaaqKh988AErVqygvb2d5cuX89BD\nD/H8889z33338eqrr5p28nAHCzkT7s2cAPp4pG0OFrt9AAcPNiSVktuTm48iNQgbZaX3ZqxglQRN\nJhhlnvfk37ixq7a2lrq6Om6//Xba29tpa2vDbreTmppq+u6i6SJglId2u50jR46wZs0abr75Zmw2\nm0edBsKo2M2ZMyeqbSAYOR6offoaG6Er7W2/fv0YOXIkP/7xj9m5cyfz58/XNws6HI5uY5zxfm63\nm8rKSjIzM1m3bp3HOOhdnz/+8Y8pKyvjtttuC2gZ186tr69n8eLFLFu2zKNMGt6rCVbDhXr7H0tl\n17oFdwmwXghRoiiKDVgN/AcwXwixEUBRlI+BfyU+FNwLQKfXZ+O/HjzyyCMMHjzY47vp06d32zgV\nSawOOL5msVbT9RqvYyWCw5o1a0hNTeWzzz5j5MiRKIrCa6+9RktLCw5HVw5v73K43W4KCwuZNGkS\nNpuN9vZ2vvzyS86fP09aWhqDBw8mLS0Nl8tFv379qKmpobCwUL9GT/mThTsgb926la1bt3p898kn\nn0SqeJKgOENXd68Cxls4rwGXqwhVVZNKwe3JzUfhWo3N5JQmBzTFINileF/XUhSFAwcO4Ha7Pdy+\nCgsLWb9+vZ66XFEUXC4XP/vZz3jggQe6xcUN10XAn+zxzlyZm5tLc3MztbW13azYZitp3s+vKXbX\nXnutrnhFg2DkeKjtU3Obu3DhAgMHDmTnzp0cPXqUY8eOUVxc7DOBRHV1NZWVlbjdbs6fP09TUxNL\nlixBURTq6+sBT59YjSuvvJKUlBQuvfTSgM+tnau54hnbq/a7WRzeQMYmX9GUNP9jK/0sWS3AVhXc\nbGAmgBDCrSjKo8Ac4F3DMX8GRkemeGHzCfADw+csoFkI8ZXZwc888wzXXHNNLMqlY7VD+5rFWk3X\na7zO008/zZo1a0hPTzdd5tOEYX19Pf379+fGG2/krbfe4osvvqC4uBhFUXjhhRf0pTPv9IcHDhzA\n6XTqUR+WL19OU1MTX375pb60uHHjRs6cOcPq1atpbm7utjTVE/5k4Q7IZpOjl19+OSRrYjxy/Phx\n3Xc6WEJxFYgM4+kKd9276YnJYqSsxoGSAATrhmTmKqVda+rUqaaJIyZNmkSfPn346quvh45BgwbR\nt29f/ZqRDBvmT/YY35vNZuPnP/856enp3bJ5gflKmsPh0BVCt9uNy+XixIkTlJSUUFxcHDVLbjBy\nPNT26X3e/PnzOXbsmB5yy5+bQGFhIZWVlXz22WdAV/YyRVFYvHgxGRkZHmOxoihMnTqVjo4OMjIy\nPHy+fbn5aW1IU261DYLG1VWr7nhm0ZTcbjelpaW4XC46Ojos9bNEdlnyh1UFNwVo0z4IIT5XFOUr\nulwSNNpDuG60eBN4TlGUbwkh/go8DLzUw2XyIFIDjrERW03Xe91117Fp0ybuv/9+XnzxxW5l0IRD\nS0sLqqqyZcsWLly4QEdHB6tWrWLo0KEMGzZM3/imWQ6gS4jdcMMNpukU4etsZvPnz+fLL7/kqaee\nYuDAgX6V8njyFeutHD9+nHHjxuNyfdHTRZFYoCcmi5GyGvuTlVbckMxcpTQ/SlVVsdlsTJo0CVVV\nPTYCORwO3G43n3/+OZ2dncybN48pU6bo5wUTNiyYsgUre7Rraxm9NLKzs6mpqfH7zgsLC2lqaqKy\nslLP2ma323E6nQwbNiyq1nx/cjzU9ul9npYGWSPQOHvttdfy0EMPYbPZdPeGhQsXdrNo79271294\nTrN2YGz/GRkZehZQs9XVQH3FXzSlxYsXk5KSgt1uJy0tLah+luxjXSiKaKWiKEb/1RTgBUVRtJGu\nf/jFigxCiDOKokwHXlYU5RLgv4CFPVwsDyK5lAVdSy733XcfN998c8A0glrjbm5uxm63A+hO9MYy\naMJhz549PPnkk/zzP/8z1dXVXHrppTzwwAPY7XbTUGWaEPP1jKqqsmvXLlwuF/v27ePNN9/k5MmT\nDB8+nNLSUgC+9a1veewKjrTgNZtxJ3oMyVigqupF5dbq0n81sDg6hZIETawmixD+JN7YR41yKRRZ\neejQITZv3gxAe3s7qampuFwufv3rX/Pxxx93s+gaNwItWbKEvLw8rr76apYvX87kyZN15dYYFWbb\ntm1MmzZNj7NqZfnXiuzxlofaZ0VROHfuXLeVNO9waHPmzOHaa6+lpKQEu93O8uXLY+L6FYwcD7V9\n+jpPGz9aW1tpaWnR0y9r9ZKbm8s999yD0+nkxhtvZNeuXeTm5gZtYVYUxdQFwuHoCtk2ceJEPSpH\nUVER7733Hu+//z6NjY0cPXqU559/nieffDJgX/EXTSk9Pd1j0hZMP7MSYzgRXRisKrhm1s/NJt/9\nbwhliQpCiLeAnJ4uRyAisZQFsGXLFqqqqsjOzg4YKNq7cW/cuJG2tjbq6uo8kjJoZWpsbOTMmTN8\n85vfZM+ePbS1tdHU1MTNN98MQGZmJtXV1UBXJh5vIaYoii4MtLI7nU6uuuoq3n777W554H/wgx/w\nzjvveOwKjjRmM+54jiEZf1hd+u8pFwWJkWhMFv3dK9xJvLGPestKbfMr4LGh1htfobWuuuoqjhw5\nwsqVK02VA+16brebmpoaZs6cyeLFixk7dmw3Gbpy5UqOHj0KdCUA0DZxOZ1Oj41NwfjXWpE9xmtq\nq2wFBQWkp6f7fOcOh0O3dDqdzrgKJRZM+zR7j77OO3jwIMuWLeOHP/yhx/nGDXZz5sxh2LBhjBkz\nxrKFuaKiIqDltaamhtOnT/P888/z2Wef6W3w7NmzHD9+nHvvvZdx48b57CuqqvqcuGjRlHJzc3W3\nsWDqM9j2lqguDJYUXCHEPdEqSG8nnKUst9vN7t27ATyCfiuK4ldp9rVr2Kxx19fX89vf/pZBgwbx\nySefMHHiRN59910qKysZO3YsM2bMAGDTpk1Al9uDty/bK6+8wgcffMDp06f12a62JKQds3LlSoYO\nHcqCBQvo378/dXV1UVk2CbQ0E+tlXIkk2bE6iffXR72tS5rcMdtQqx3jHVqrqKiIK6+8ko6ODsrK\nynSLrvcGs6effprx48eTl5dHbW0thw4doqmpiVOnTnnskF+5ciW33XYbO3fuJCsri7q6Oo4dO0Zl\nZSV2u10vf2tra1D+tWBt01x5eTkjRoygvb1df1+ZmZnMmDHD5zvXLLnGUJOJghWl6y9/+Qu/+c1v\nGD16NOnp6ezfvx/oWrE0brDT2pW/LGfQvS0Ha9n93ve+R1ZWFtu3b+fzzz/nxhtv5Ny5c3z66ae8\n8847QFeWNbO+EmjiYiyzMSRafn5+t7Bnxufw194S3YUhXnxlJRbRNgm0trbS2dnJokWLgK6GZyUW\npNE6UVdXx5EjRzx8lzTBWVlZycmTJxk4cCC//GVXgIxLLrmE8+fP8+ijj3LTTTfR3t6uB12vrq7m\n17/+NRMnTgS6lu7+f/bePiqq6174/xwccER8GR1FTSQQyqOWoHeJcRVb5TY16Y1tchPy1FSjZDXL\nSw2pxJiraXzJg9Ukjc/VIDQUqbGIRhNvL7Favc3PvCwxhVtySRrtU0i5ijXeC2yG5swAACAASURB\nVMgoxpc4wuj+/YHn5MwwL2feYAb2Zy0WMHPOPnvO7PPd3/3d3xdV0LsmUNdvs5hMJu666y5++ctf\n9tguDOW2iZGtmd7cxpVI+jv+LuKN+CM2NTVRX1+vyZ13332Xjo4OzS9VlRH6kq2xsbGcOnWKoqIi\nBg8ezJgxY7T21WIJeuvw1q1bGTZsmBbT4GqltVqt7Nu3j+bmZg4ePIjZbGbLli2cO3eOrq4uvvzy\nS8aPH89Pf/pTAO655x7AmH+tN9mjWq6zsrJoa2ujo6NDczdQYy/Uz+NaftjdtaIFT0qXoig9FLnP\nPvuMkydPUllZSWdnJ9u3b+fGjRv88z//M4qikJCQwJdffklBQQGPPPIIiYmJXncBVNy5h/iy7F6+\nfJl33nkHgBEjRnDu3Dm2bdtGbGysNg9u3bqVjIwMDh065DXwzNvCRXWLUHcObr/9dp8LAU/jLdrd\n9aSCG6WoxRYKCgoYMmSIJjy3b9/ud/EG9YFQJ4ArV65oya6vXLlCVVWV5j7wP//zP5jNZs3Pa8KE\nCXz55ZfaFiFATEwM//f//l+EEJSXl5OQkMDvfvc7zb/2/fffB9AsH67bLPrUJ762TQLN4Whkayba\nBL9E0p8w4o/44osvOmXyeO6557BaraxZs4a8vDyampp48cUXKSsr03xpn3/+eYYPH87PfvYzMjIy\nPPqpNjY2UldXx82bN7XMJzt37uShhx7SrLRqBL0arZ+cnMyWLVsYOXIkV69exWQy0dXVRUtLC0OH\nDsVkMvVI57Vw4UISEhIMbbXrUZXvHTt2YDabsVgsWrqrS5cu8eqrr2K1Wlm9enVY3bx6G71xR19N\n7sEHH+TAgQNOityGDRuoqqrC4XAQGxvLhQsX6OrqIikpiZs3b2Kz2ZgwYQJms5kDBw7w5ZdfOu0C\n+GtEcXXDc81utHLlSgDKysrIzs5mxowZnDlzhu3bt7NkyRLOnz/Pf/7nfzp9X96UTE+7FXV1dfz6\n17/GZDJx7Ngx7HZ7j7RnejyNt2h315MKbhSirug6Ozsxm83Y7XbuvPNOLBYLFRUVbos3ZGRkuPVT\nU60go0aNwuFwaKvc+Ph4du/e7VTLe+3atUyYMIENGzYAsG7dOsxmMy+88AKxsbF89NFHlJSUcPPm\nTcaOHYvD4eCdd96ho6ODwYMHM3bsWM2/Njc3l3vvvZe6ujqP2ywq3rZNAs3hKN0QJJLIxtczqgbv\n1NfXU1RUBMDy5cvJzMxk1KhRNDY2cvToUVpbW/n0008ZOXIk165do6uri8TERMaOHatt9UJ3DIGa\ng1tfuerChQvs3r2bCxcucP78ec1Kq88ak5eXR35+PqWlpdjtdlpbW9m6dSudnZ2sXbuW8ePHs2HD\nBpKTk3so1B0dHSxbtsywf+Nnn33GW2+9RXJyMhaLxSkl5MaNG2lra2P58uVcu3aNzs7OHsUfokU5\n8YTeuONwOFixYoVmzAFny/i6deuYPXs2hYWFXLx4kfnz5/P73/+e1atXa23Exsb2CPxSz/fX91Q1\nzFy4cEGrmKaOWZPJxNy5cwGoqKjg//yf/8PkyZM5fPgwv/rVrxg1ahSHDh1ycmdRjU9GlUz9jqua\n9qyoqMhj2jNf9OY8GY5ANqng+iASowf1KzrVQrBq1SqmTJmibVu4bmvU19dr2/76FapqBWlvb0cI\noaX/2rBhA0OHDqWpqYmZM2eSmJiIyWQiNzeX6dOnc+jQIR555BHeeecd0tLSsFgsnD9/nkGDBjFq\n1Ci+//3vU1lZyQsvvIDFYuHnP/85JpOJsWPHcv/993PfffdRU1Pj0z/M07aJrxyORr836YYgkUQe\nrs+vt8h4i8VCWVkZAHPnzmXy5Mls2bKFHTt2cOnSJRwOB6WlpZpCGhsb65RGSS3jCmjGgNbWVp59\n9lmOHz+uVaxKSUnhxIkT3H333W6zxqgZGiwWC19++aXm0wvwyCOP0NLSwr333qsp1fpUiWDcv/Gt\nt97ilVdeISkpiS+//JLt27fjcDj44osviIuLY8iQIcTHx2spFz3lNo+0ec0I7ow7H330EceOHXOb\nAWPevHkkJiaSkJDAhQsXGDduHHFxcWRkZJCWlkZubi6/+tWvKC8v57//+7+dgg/V4kTgu6xwaWkp\nV69eJT09HYfDQXFxMZ988gkZGRnaOfoxrPeRTUpKIi0tjddff53z589rWYTU+Va17hspZlJVVaXt\nuE6YMIHW1lZGjhyJoihOFdT8pTfmyXAEskkF1we9GT1oVOi4rujU6mKrV69mw4YNWK1WzfdHVQI3\nbdpEW1sbI0aMcPJTy8nJYeLEibzwwgscP36cmzdvYjKZuH79Ol1dXdqqb+HCheTn5ztF6ZaUlJCa\nmkptbS179uzB4XAwatQohBAcPHgQh8PBlStXSEhIYPDgwVy/fp1vfvObfPDBB9x///1axgdfCq67\nz+8rh6Pr9+YrEbtEIokc1Oc3IyODEydO+HSxeuKJJ7S/odvNSpVhAF1dXQwZMoTvf//73HPPPU75\nuI8cOaL5sUK3MaCsrIwRI0ZohRxUq21eXh4zZ84EnNMdNjY2smvXLs6ePcuZM2dISkqisLAQ6E51\n+NBDD7Fs2TLNuJCXl6fJTRVv/o16f9vk5GRSUlLIyspi9+7dPPnkk2RnZ7N582ZWr16NyWRi4sSJ\nmuzv6upi69atTsp4tEXFu/OlVo07H3zwAfPnz2fq1KlOFs7Dhw9rriUmk4khQ4bw5ptvMmjQINra\n2rBYLNx3331cvXqVrq4uSktL+fLLL/nJT37C559/3qM4Ebh3J7HZbGzbto0LFy6QnJyMw+Hg7bff\nRlEUbcHjOs/ofWRzcnJQFIXhw4cTFxfntMuZlZXlZN33pWTqdYO1a9dy2223sXLlSn75y1+6TXtm\nlHDOk+EMZJMKrgf6InrQqNBxDQ6Li4vrsRWVnZ3NnDlzKC4u5vXXX0dRFGJiYrhy5UoPP7WUlBSu\nXLnCuHHjuHHjBkOGDPGY7FrvGrBr1y4WL17MqFGjNDeGp59+mtjYWBRFwWQysXnzZmJiYhg+fDiK\nolBdXc2NGzcM+QV5+/yecjgqikJtbS27du1yyijhLXJZIpFEBu52nsrKyjRLmDusVqtTqVybzcbx\n48cZNGgQMTExCCGIiYkhPj6e5ORkJ0sYwOuvv86+ffswmUw4HA6Kioq4ePEi2dnZTJs2jddee62H\nHNQrGuqO0vXr1xkzZgznzp3j888/5+GHHyY3N5eRI0c6WWknT56s5S1X5aaRrWfV31a1VL7zzjt0\ndnby6aef8tBDD/Hiiy86xS4UFhZqhg9VGf/ss88oLS0lOTlZ6496DyNZLqpzY0lJidM90yvurumx\nrFar07xktVp7FD9KSUmhoaEBu92Ooii0tbWxdetWFi9ezJtvvqn5zs6aNYvFixcDaArn+fPn2bFj\nBxaLhbi4OEaNGkV8fDyffvop0G2hf//996mpqSE/P98paEwfdJ2cnMxLL72kZRFydWcB53FjVDdQ\nLcB///d/j6IoEfv9hjOQTSq4HujN6MHPPvuMHTt2cO7cOSelzJfQsVqt3HXXXdqq3V0/Fy9ezPvv\nv8+8efPYtWsXCQkJPPvss05+ao2NjQwaNIgJEyaQmprKn/70J7fJrvURoQ6Hg507d1JdXU1BQYF2\nT9Rk06dOnWLVqlU8+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/2NGzeyaNEiqqqqnI7zpeCWl5cHFPjjbxtCdFdBU/uhChNfk4K+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JiorqVsewUIq+IZGECs6cxezHKUd9PT8/n82bN9Pc3Kyl+j5//jxCCHJycjTHUvsQi6ri/Kc/\n/Yndu3fT3NyM2WxmzZo1GI1Gh/JEdc5ylAFNrWdFRQXbt29n4sSJmqzwVi4dPHhQS3zTVQftYBjr\nAqFk+5zJTAhxCfjAbzW5wrBf5emK574vMyB9eREREVy8eJFbbrmF/Px8LSSKvYe5syD59ugFkcVi\nYeXKlVo9y8rKALj55pupqKhwmanFarWSnZ2txfDzpeHr07CuWbPGYczVKx1vJ0jeRhUwm8189tln\nNjGX1UQNFouFxx57jGnTpgHQ2NhIWFgYdXV1rFmzplOMZn3qXUCbMAGMGjWKpqYmGhoaGDRokJaz\n/u233+6UGCIQhGL0DYkkVHAmp5xFQnHU51pbW2ltbaVv374YDAa+/fZbbbzUh1gEbPrysGHDeOCB\nBygpKeH48ePce++93HrrrSQkJDisq/0k115mvvTSS9TW1nLfffcBvsmK7oxw0B0EQsmWqXp7CHcd\nwJfZmDczoKKiItavX4/VaqW5uZnGxkZ27NiB1WrlwoULQHun1oc/Adsg+c46o32g6aeffhpoX7XT\nKzYVFRUuM7VYrVa2bNmiJYDwpfHr62g0Grn11ls7xVz1N6G2Re3tBMlTwapX+Oxta9XsP3qzmIaG\nBr777jtOnDjR6Xi1Ths3brTpJ+qEafLkyRQXF9PW1kZraytXXXUVf/zjH2lubqapqcnnbS9v3qUM\nJybpCr5kUDOZTMTGxgagNsGFvh/a24va4+hzNUxgQUEBL730Eg8++CB333035eXlnSbN9qEJAdas\nWUNDQ4OmHO/Zs4d9+/Yxb948m6REzia5asxwdaElLi6O2tpaPv74YwYOHOg0kYQrArm131uQCm43\n464DdGU25s0MKC0tjfr6evLz8/n6669RFEVTbN944w127NihdTZnQfKddUZ9xzMYDEydOhWAvLw8\n7Z70Wars65WcnMzhw4dZu3YtMTExzJ8/n+TkZM0w3xfUZ5OQkBBwW6NQ3aL2ZoKkZqAD54LVkcJn\ntVq57rrrKC8vp7CwEGifyCxdupTTp09rZiRqKkuAFNlQ7gAAIABJREFU6667TquTvXKtTphqamr4\n4IMP+MlPfkJBQQFCCB5++GESEhKorKz0+T148y5724qKpLs4BfRh9uzZXp9pNIZz7Fhlr1dy7fuh\nN46iej+TiIgIDAaDFrM9IyPDqZxKS0tj/PjxLF++nAULFmgxt5ubm5k9ezZTpkzREhipuJvkbt++\nnZqaGqxWKwkJCTQ3N1NTU8NDDz2kJdTxllD0Fek23IVZuBJ+6GKYMG9wFxKjO0MRNTY2iuLiYhEX\nFydGjx6txenbsmWLTaiQroSgUkOL6P92d48bNmwQSUlJIjw8vFMoqWDGk+fUG0I3qe+vrKzMZegY\nV8/DWczJxMRELabtggULnLYz+zakj0Gpbzu+tpmuhIoLlnBivaGtdYXQCROmnlfQca6nP8HzfoMt\n/KGeyspKERsbq8Wa1ceq1Y9JjsrQn5uSkuJWtrirb1VVlVixYoXYsmWLSElJETk5OSIpKUmUlZX5\n7Zn1drwJExZSK7iKoowFGoQQlp6ui6+4W+XxZjbmzfapo2NNJhOTJk3ikUceoaioyOn2va82vvbl\npaWleWSjqK7ibt26lbKyMpcrYcFkDtDbt6jtdx9Onz6t2as5wv69RkdHU1paqoV/KSkpoba2lpaW\nFl5++WUGDBigpbrMzc1lzpw5TtuZfT/RZypzlH/dW7ryLuWKisQ3vM241vvpSj9U5VVFRQVtbW3M\nnj2biIgIG1M5vYw6cuSIjTmUyuOPP65FGdLLlqFDh3ZySnM3Vo4dO5bnnntOk6EpKSlkZmb6LKdc\n3XuwjIs9ijsNOBh+gBXAcaAFmGT33RPACeALIAtQOj6Ppd0J7iTwV1xo+3TjCq6KP1Z5vLmGu0wv\nasYqdytyngZ7dlSetwGd9ddwVnawrJYJ0ftXcH3Nlqa+OzXgeWVlpZaYJD4+XsTExIiysjKPV4Zd\nUVZWJmJjY7u8IhKq2cv0hHJb8weht4IbugkignEFV5VX+lXXpKQkERsb6zS5gydZEFX5pJdnjurt\nr7HUF4JpXPQ3vXEF9xCQA1ToP1QUZQrwOO0K6gXgI2A2sBXIA/4ghLhNUZSfAtuB0d1YZ5d0ZZXH\nG29tT47V2+7qDead1dlRfdTZovq/o/K8tVHUPyN7G6xg9Fjv7Ub/XbEx1YeN27VrFw0NDVgsFtra\n2ggLC+PgwYNMmDCB9PR0xowZ4zZSh0qgVip6+7uUSEKBrvTDKVOmMHLkSA4dOkR2djb33nsv48eP\np7q62mHUHoPBwPjx420SPtjLl3nz5nH27Fmys7OZP38+4H5MdXZfgdjVC8ZxsScJCQVXCLEfQFEU\nxe6rnwIFQogzHd+/CdyvKMofgZuBuzvO/72iKNmKoowXQhzpxqo7xRNl0R9hmrq6be5JffTKZ2lp\nqcvy3Akr+/KcmTWUlJRoTkr25djHIOxuQm2L2hslUe9cZm9y4Ay1DVqtVk6ePMlzzz2H1WoF2oOV\nA/zqV79ixIgRLFmyxKvnpo+HqyaSiIqKchvpw1NC7V1KJL0RX/rhwYMH2bhxoxYBSB/5QL2OGk3I\nYrEQGRnpNN62urAyefJksrOzqampYe3atZozrD4Cgj+TFKlJIA4ePCgjufhASCi4LkigfWVW5QRw\nNXAtcFoI8a3uu5Md3wWFgusMT7y2vVlJ66pnt6P66DueELYZZJKTk22C9jsqz5Ww0issRUVFXLhw\nwaEim56eTkFBgcP76ukoBoGanQcKs9nM+vXrqa+vd5kuWX2uOTk52v05es6OJimTJ09m//79LFq0\niF/84hcAvPPOO9oK7sKFCx16Jbuqs37iY59AxF+CPdTepUQSjHRV6fOlH+pjoC9btsxh7PO0tDRG\njhxJZmYmVqtVs811FToMID4+3mkEBH+NP+p1Ro4cGRSRXELRrjdoFFxFUVYC99FuWwHtqX8bhRC3\nuTitDWh18L/9546ODSq82VrwZtvG2y0eV8qrej2149XX17N7927tXL1SoTofOSrPXlg5Shd8+PBh\ncnNz+fWvf+1UkbW/L7VucnvGM+yTauTn53PjjTd2GgTs22Z1dTUjR46kuroa6PycHQl4i8XCRx99\nBMC1117LtddeS0lJCa2trfTv35/77rvPKxMA+5UKdwlEukIoCnaJJJjoiUUHvdyPiorq5DytyrXL\nly9jNBppbm6mX79+mEyO49LrQ4etWrWK+fPn2zjDqjLSm/HHkWw5duwY77zzDsOGDaO5uZlDhw55\nlV4+UKZVPb1w5AtBo+AKIZYBy7w87UvgGt3/1wC1HZ+PUBQlTAjR0vFdbMd3TnnyyScZMmSIzWez\nZs1i1qxZXlbLe3zZWvBm28bRsY46lzPldfny5Zw5c4b09HTNPjIuLo7nn38es9lMdnZ2J6XCVd30\nZZvNZtatW8fmzZsxGAxYrVbWrl3LqVOn2LNnD5mZmVpiAPsOq7+vYNue2bZtG9u2bbP57Msvv+z2\nejjDPtnHqVOnyMzMJCMjw2Yl1/65Llu2TItJrE+Dm56erkUyAFtzks2bN3P8+HEiIyO1dMnXXXcd\n48ePJyIiwmGaTHv0bcZZPFx9AhG1TfhjqzDUBLtEEgwE0ibU1cTTke2s/TH2KcpbWlp49tlnWbhw\nYSf5kpmZSW1tLTNnzlQd0ztFQPBl/HEkW9555x1Wr17NkCFDOHfunJau3JP08ir+NK0Kabted15o\nwfQD1KCLogDcAXwODAEGAJ8Ad3Z89xfgFx1//xQod3Hdbo+iYE9PeG3rPUerqqpsyt+yZYsoLi62\nidf3ve99T4wdO1bznldjCi5atMhrj0217OLiYrFz504xYcIEkZOTIx544AExYMAAkZCQoMUtTElJ\nEVlZWW69TkPB8z2YPNsbGxvFihUrtLiz+meuj4xg/1zt24b6nLOysjpFWJgwYYJYtGiRyMnJEQkJ\nCSIhIUHk5OSIsrIym/fiSfQDR57B9p95E2/Z0fPQt7FQaE+uCKa21hPIKArdh7O25mvkFU9w1b9d\nyQUVff+eMGGCWLBgQSe5pF6nuLjYbUQfb+SFo2PLyspEWVmZ2LJli0hKShKZmZli9OjRIjMz02F8\n+u4ikO/QF3pdFAVFUbYBNwLfA36vKMp3wE1CiH0djmWfAn2AN4UQf+o4LQPIUxTlaeAr4KEeqLrH\ndKfXtqOt6cbGRg4dOqSlJlRnjbfffrtmpB8VFcXcuXOB9rS7c+fOJTc3lx/84AckJCR4NJvTl22x\nWMjMzMRoNGIwGMjLy+PChQtERkbyxBNPkJeX59QkwRHOnqE6S5ZbzLaYTCYWLlzIjTfeqL2HVatW\nObSZ1v+vbvWpM3n1OZtMJm0FVzUn0ae8NBqN1NTUkJubS2ZmJqmpqVp7OHz4sPY7MjLSpkxHKwgW\ni4Xy8nLuvvtum5UKV46J7tpQINJnSyRXMoGwCXW1oqh+b/9dTU0NL7zwAsnJyTayQv3barVqKeH1\ndVMUhenTp2uRFaqqqkhMTHQ4lngzhjuSLY2NjUD7OGs0Gjlw4ABff/01bW1tGI3GgKaXd0UoZ2gM\nCQVXCOHURkAIsRpY7eDz44DzKPRBSnd4bTvamn7//fe55557mDhxoo25wfbt223S9Obl5XHx4kXO\nnTsHgNFo5LvvvnMZ8N++bLVjR0ZGanVoaWlh3bp1REdHU15eTkpKipba19tObf8M5Razc0ym9mQf\naspKd/bc9sqk/f/2Av6WW25hxowZThMw5Ofns3nzZm0StXbtWnJzc3n00Ud56qmnAMeDQXNzM01N\nTUybNq3LkUMCmT5bIrmSCcTCjav+Ddh8t3z5cqxWqxZlxX4CbTabsVgsTJ48mbKysk6T4YMHDzr1\nM+mK6aAjpVE1w1MdtBctWkRtbS133nmnjWLe3XTn4pu/CQkF90qiO7y209LSqK+vJz8/n1OnThET\nE4PRaOTQoUNERUUB/2zECxcu1BQUtSOWl5fz1ltvaUqvNytbjmwn+/Xrx7PPPquVqa7s+aroq8/Q\nF6P/KxF1JXfEiBEun4t923TWVvUCXv+sDQYDmZmZXgtHfZtZvny5zS6Co3fq7YqDpwpxKAl2iSSY\n8OfCjbv+rf/u+uuv5y9/+Qsff/wx0HkCbW+Ha9/3fVm99GQMd6U0qjJNXXgAuOmmm3x5VH6lOxbf\n/I1UcK9AXG1NK4pio+g4W5V75JFHfFrZsr+eumKbkZHRaVu8q4q+3GL2HH9OrBxdy5lwVFPs7t+/\nn8WLF/PEE08wdepUm9V31VlEdSLLzc3VzFocvVNvVxz8mT5bIpF0xt/yxVX/1n83fPhw+vfvrzmG\n2eNsJbW8vFxzpA3k6qUj2RKs8qY7Ft/8jVRwr1Dst6b1Qfu9WZUD3zq9vrMUFhZSUFDg9w4dyrZD\nVwpqW7JYLJhMJlJSUjqF8tGbl+jzwrt7p54OFJ4MmKEm2CWS3o4jUzT7yAlTpkzhkUcecTqBdtT3\noX1MmjZtWsAnua4WAyRdRyq4VzD6rWlwHLRff6ynq3KeoiqfEBjzgVC2HeptuLODHjNmDEuWLNFs\ncx3ZxSYmJmor/fYObo7wdqAI1pUTiUTSGfv+rZcxiYmJNt85m0Drr5Weno7FYtFisduPSVLpDD2k\nghsk9GQweV8Vza50+u40H5CKS8+hKqoVFRU0NjY6DVZu35bctY9AvFM5iEkkoYd9VKDs7GzNkVWV\nD/YTaHtMJhMRERE89thj2mfSpC30kQpukNBTnv7eKJreKuGuju9O8wGpuAQGT9qD2r6am5sxm82s\nWbMGo9Hotn15ahcruTKoq6vTQjV5SmVlZYBqIwkm9GOY1Wply5YtWsgvvV2+tw7Q3ZUNUWZKDBxS\nwe1hejpLSFpaGsnJyWzdupWysjItI5SjsqurqzvFEnSFK6XdV/MBT4SBFBjdgyeTsilTpjBy5EgO\nHTpEdnY2t99+O21tbYwfP97l9ezbYFfNS3yZnOXn5wN0coCUdC91dXWMHTuO5uZLPV0VSQ/hbrEk\nOTmZw4cPk5WVxcCBA5k9e7YWGszTvutvk7Zjx46xcuVKli1bhhDCqayUYSwDh1Rwe5ie9vQ3mdpj\nAX744YecO3eO6OjoTp3ak2D8jo73RGn3dqvZnTAwm82sX7+eoqIiKTACgKr4qY5e4Pr9Hjx4UFvB\nhfa0vV9//TVRUVFa6Bt37cVd+/B00uPNIGI2m9m8eTOAjbOJpPsxm80dym0BMM6LM0vwPvu7JBiw\n79PuFkuKiorIzc2lvr4egIKCAnbs2OHTOOrNmORK9nzxxRcUFRVx6623ajFuPUlK0V2LW1cCUsHt\nYXrS099esWhpaaG2ttbGdgk8C8avxxOlXS8YPBFAnijNqq1nfn4+RqNRCowAYDabWbduHZs3b8Zo\nNAKuJ2Vq+z5w4AAvvPAC06ZN409/+hM1NTWUl5czZswYt+3FXftwNfh5u0NiNpuprq7m8OHDWnvf\nv38/FoulU7+QdDfjaM+q7inSRCFUUfu0ugrrrv9OmTKFQYMGkZ+fz8GDB7n33nu59dZbSUhI8Lps\nb8yfHMmejz/+mLfeeos+ffrQ2trK8uXLiYiIoH///i6TUkibX/8jFdwexpdtEX9tweszmrW0tHDp\n0iWWLVtGdXU1CxcudHhtIQTnz58nLCzM6XU9Udq9XVFzpwSpK7f65BVLly7FYDCwcOFCKTC6yLFj\nx9i8eTMNDQ0MGjSI+fPnA+3JFlyZtajte/v27Zw7d44DBw7Qt29ftm/fzieffEJmZqbPkzxPlFdv\nd0iKiop44YUXbOw9Fy9ejMlkYsmSJbIdSSQBxL5Pb926ldLSUgwGg8ukQvqdIkVR2LNnD/v27WPe\nvHmMHTvWp3q4GmNdyZ4XX3yR4uJiwsLCEEJgsViwWCwMHDiQN99802lSChnG0v9IBTdI8HZbxB82\nO84ymhUVFTFixAhNgOiD8T/99NMYjUaysrKYNGmS03txprT7anPsTgkqKiqiqKgIo9FITEyMdj8Z\nGRmkpaX5/Iwk7bzzzjtkZ2cDkJCQQF5enpYu15NJ2cyZM7l48SKRkZFs2rSJmJgY5s+fT3JyMoDN\n+Z7avnmivHqrPOvt+dauXQvAE088QUpKilMPbIlE4h/s+3RZWRkAN998MxUVFU77r9rPKyoqWLZs\nGYsWLWLSpEk+j4/uxlhHssdqtZKWlsZdd91FZWUl8fHx7N+/nwcffJBbbrmFnJwcl0kpZBhL/yMV\n3CDBk20RfzukmUzOM5rZh3ACGDZsGIMGDSI8PJzLly9rq1zOynaktPtqc+xupVuvyCxdupSYmBiy\ns7O7JOQk/9yy79evH1FRUbS0tHD+/Hlmz57NhAkTqKys9Oj5jh07loSEBLKzszl16hTx8fHk5eWR\nl5fnc+gvT5RXb3dI1OMjIyPJzc0FYOrUqXLgkUi6AUep3NUMhhUVFU77r76fR0VFMWnSJJ/6rKdj\nrCPZc+TIEYqKigDo378/R48eRQjBN998w/jx43n00Ued7nLJMJaBQSq4IUQgHNJMJtuMZs4EiGrO\nMGDAAE0Rdle2I6W9qzbHzoSBXgAZDAYyMjKkcusH7Lfs29rauHz5MtnZ2SxfvtyhDbYz7CN2dDX0\nlzfKq7eDiMlk4tFHH9X+lkgkgcdZnzabzR5nJeyKsujpGOuonrfccgszZswgOzubLVu2MGzYMIYM\nGcIXX3zBY4895rRe3so9iedIBTeECJRDmrqSO2LECJdbt/4o2xebY/vz3a30Lly4UIYI8xP2W/at\nra3cdNNNZGRkMHHiRK+upV8ddbUa4y2eDGq+KM/eKO8SicR/2PdpT/tvV5VFb8c5fT3Vnzlz5lBa\nWsr8+fPJy8uTtrU9iFRwQ4iuKofurt0VEwFfy/N3p5ezYf/iaMv+V7/6VVC9e/nOJZLeRU/1aV9M\nmuzrOWbMGDIzM0lOTiYvL0/a1vYgIaHgKooynfaAhlcBl4GnhRAlHd89ATwJWIFdwH8LIYSiKLFA\nHjAGOA3ME0J82gPV9zs9abPjr7KlUhJa+HPLXr57icR/+JKxzWQyERsbG4Da9A66Ms6p53pqViEJ\nHCGh4AKDgbuEEN8oinI78K6iKJHAZOBx2oMjXgA+AmYDW2lXbv8ghLhNUZSfAtuB0T1ReXd4G/ar\nJxUEqZxcmXR1y15ml5NI/M0poA+zZ8/2+kyjMZxjxyqlkusEf4xzcqz0HX+NF338WKeAIYQoEEJ8\n0/Hvx8BAoD/wU6BACHFGCPEd8CZwv6IoUcDNwOsd5/8eGKgoSuf8oEGAGpLE21zrEkmoINu4ROJv\nzgJttGd4O+zFTwHNzZdkX5QELf4aL0JlBVfPz4DfCyGaFUVJoH1lVuUEcDVwLXBaCPGt7ruTHd8d\n6baausHfYb8kkmBDtnGJJNB4m+FNIglO/D1eBI2CqyjKSuA+QKgfAY1CiNt0x9wPzAF+0PFRG9Cq\nu4z6v/3njo7tcQIR9qs7kNvNEk/pShuX7UwikQQjUjYFBn/rREGj4AohltHuSOYQRVEepN2Z7E4h\nxLmOj78ErtEddg1Q2/H5CEVRwoQQLR3fxXZ855Qnn3ySIUOG2Hw2a9YsZs2a5fmNeEGgwn4FGn9l\nUuvtbNu2jW3bttl89uWXX/ZQbXqGrrRx2c4kEkkwImVTYPC3ThQ0Cq4rFEVZAMwEbhNCnNd9tQN4\nQ1GUbNqjK8wFlgghTimK8int5gyvdziZnRBCfO6qnNdee40bbui+rZ5Ahv0KBHK72TscTY7eeust\nn5xCQhVf2rhsZxKJJBiRsimw+FsnCnoFV1GUq4E3aLeh/auiKArtZgxjhRD7FEV5E/iUdoe5N4UQ\nf+o4NQPIUxTlaeAr4KHur71nhEqqvlA1qZD0PN60cdnOJBJJMCJlU/fgL50o6BVcIcRXuIj2IIRY\nDax28Plx2sOIBT2hEk4kVE0qVKTdVM/hTRsPpnYm24xEEnoEqt8Gk2zqzfhLJwp6BVcSPISaSYU9\n0m4qNAimdibbjEQSegSq3waTbJK4Ryq4Eq8JFZMKFWk3FZr0ZDuTbUYiCT26q9+G2hh4pSIV3BAi\nWLZLQ8WkQkXaTYUm/mhnvvYZ2WYkktAjkP3WXpZIORD8SAU3hJDbpb4h7aauXHztM7LNSCShRyD7\nrRx/Qw+p4IYAcru0a0i7qSuPrvYZ2Wb8T11dnU+pNysrKwNQG0lvJBD9Vo6/oYtUcEMAuV3qH6Td\n1JWDv/qMbDP+oa6ujrFjx9HcfKmnqyK5AvBnv5Xjb+giFdwQQG6X+gdpN3Xl4K8+I9uMfzCbzR3K\nbQEwzsuzS3CR5FIi6YQ/+60cf0MXqeCGAHK7VCLxDtlngpVxgLfZIqWJgqTnkLIkdHGaQEESfPS2\n7VLVaN8XuzyJRI+zttTb+oxEIukZukuWyHHRf0gFN4TobYO17MgSfyEVXIlEEkikght6SBMFSbcj\nvVIl/kK2JYlE0huQssz/SAVX0u1Ir1SJv5BtSSKR9AakLPM/UsGVdDvSK1XiL2RbkkgkvQEpy/yP\nVHAl3Y70SpX4C9mWJBJJb0DKMv8jncwkPYZ0AJL4C9mWJBJJb0DKMv8REiu4iqI8AjwFRABfAf8l\nhDjW8d0TwJOAFdgF/LcQQiiKEgvkAWOA08A8IcSnPVB9iRNkEH2Jv5BtSSLxDl9SIJtMJmJjYwNQ\nG4mKlGX+IyQUXGCvEOJ3AIqirAGeAx5UFGUK8DjtkcMvAB8Bs4GttCu3fxBC3KYoyk+B7cDoHqi7\nRCKRSCRBwimgD7Nnz/b6TKMxnGPHKqWSKwkJQkLBFUJ8DaAoSjhwNfBJx1c/BQqEEGc6vn8TuF9R\nlD8CNwN3d5z/e0VRshVFGS+EONLtNyCRSCQSSVBwFmjD+7TJlTQ3z8ZsNksFVxIShISCqyhKBPAp\nEAvsBtZ3fJVA+8qsygnaFeBrgdNCiG91353s+E4quBKJRCK5wvElbbJEEjoEjZOZoigrFUU5qijK\nkY6fo4qifAAghLgghPgX4CrgS+D3Hae1Aa26y6j/23/u6FiJRCKRSCQSSS8kaFZwhRDLgGVujmlW\nFCUb+EfHR18C1+gOuQao7fh8hKIoYUKIlo7vYju+c8qTTz7JkCFDbD6bNWsWs2bN8vAuJJJ/sm3b\nNrZt22bz2ZdfftlDtZFIJBKJ5MohaBRcVyiK8gMhxJ87/n2QdmcygB3AGx1K72VgLrBECHFKUZRP\ngZ8Br3c4mZ0QQnzuqpzXXnuNG26QWzYS/+BocvTWW2/55NwhkUgkEonEc4LGRMENjymKclJRlGPA\neOARACHEPuBN2u1z/w94Twjxp45zMoAZiqKcoD2M2EPdX22JRCKRSCQSSXcTEiu4QoifuPhuNbDa\nwefHgcmBrJdEIpFIJBKJJPgIlRVcSZBhNpvZuHEjZrO5p6si6eXItiaRSDxBygqJnpBYwZUEH6og\nmTx5skwpKAkosq0FF3V1dV4rEL5kzZJIvEXKCokeqeBKvMJsNmM2m6mqqgLQfptMJilQJH5FtrXg\no66ujrFjx9HcfKmnqyKRaEhZIXGEVHAlXlFUVMTGjRu1/1etWgXAvHnzZP5siV+RbS34MJvNHcqt\nt1mwSnATBVIi8RkpKySOkAquxCvS0tKYPHkyVVVVrFq1iqVLl5KYmChnyRK/I9taMONtFixpoiAJ\nHFJWSBwhFVyJV9hv+SQmJpKYmNiDNZL0VmRbk0gkniBlhcQRUsGV+ITJZGLevHlyhiwJOLKt+Z/v\nvvuOX//611y8eNGr8+rr6wNUI4mk60hZIdEjFVyJT6iCRCIJNLKt+Z+CggKWLVtGWFiCV+e1tloC\nVCOJpOtIWSHRIxVciUQiucJobW0F+tDS8v97eearwP8XgBpJJBKJf5EKbjvDAd577z0Zr1ESUIqL\niwEoLCyUbU0SUFy1tU8//RRoQ1EGeHVNIVo6/toEfM+LM//h43ldOVee59/zvgagpKSkU3uSck3S\nXRw7dkz9c7i7YxUhRGBrEwIoivI68POerodEIpFIJBKJxC1vCCF+4eoAuYLbzvvAzwsKChg3zpvY\njp7z5JNP8tprrwXk2j1VVm+8p0CXtWvXLlauXIm/21p3Ph9ZXmiU15W2Fuj7l9fvXdf3pq31Fll+\npZUXLPdWWVnJ7NmzoV1vc4lUcNtpABg3bhw33OBNbEfPGTJkSMCu3VNl9cZ7CnRZ6vadv9tadz4f\nWV5olNeVthbo+5fX713X96at9RZZfqWVF4T31uDuGn38V53AoyjK64qi/K+iKHWKorytKEq4oij9\nFEV5U1GULxVFqVIUJUN3/G2Kovyfoii1iqK8pyjK0J6sv0QikUgkEokk8ISUggu8JIRIAuKBUcCD\nwDNAVMf/04B1iqJcoyjKYGA78IgQIg44CbzSI7V2g9lsZuPGjZjN5p6uikQSEGQbl+i5fPmybA8S\niSSghJSJghDiq44/hwMDaXcHfRx4XLR7yx1XFGUv8GPaXT4rhRD/03HOG0AZ8Gj31to96uA/efJk\nGaBa0iuRbVyiR1VwZXuQ9Bbq6uo4d+5cR4QSzzGZTMTGxgaoVlc2IaXgKopyG7AZiAaWCyEqFEVJ\nAI7rDqsDrgYG2H1+AhisKMoAIcS33VVnlVmzZnX6zGw2YzabqaqqAtB+26cd9EdZgaC7yunNZfmL\n7q6zp+X5q40H6/2FannuCFR91PZw/fXXc/DgQb/JPHsC/Tzl9UOj7O4qq66ujrFjx9HcfImUlBSv\nzjUawzl2rNInJbc3Pkt/lheSYcIURYkGtgF7gJXA94UQdR3fvfz/2Hv/6CjKe/H/NWQJC0RxYUOC\nAk0aU7AYUhvhNN5C2guVIxZqc+83CMXYqsVAS1B6i8oPGwVpjRcMoWLIBxECgkZdKQicFtQS2qQ3\nmqsFbxNNIREtZJOFDRJgSZbM948w4+5k9leySXY3z+ucHMJmZ+fZmfe8n/fzft4/gHbADtwiy/ID\n1143AheBIbIsX9F83reBqqlTpzJs2DC3c839+cJXAAAgAElEQVSdO7fHbmxxcTHFxcWdXl+wYEFE\ndWOx2WxYLBYyMzP7lbdm9+7d7N692+21L774gg8//JCqqqpeDdjvKzzJ+Lx584iJiel3MtGbvPLK\nK8yfPz+kZC2UdV5/1VPBIBRlrTf53//932uG7U4gkIol1UD/vW5d4atrTZosy17d5WHlwVWQZdkq\nSVIJkAl8AXyNDs8t135/D7gA3OVyWAJg1Rq3rjz//PO9KmSZmZlMnTqVmpoa1qxZw8qVKxk/fnzE\nKdf+uj2ttzhSJoL+gicZt9vtLF68uN/JRH8nlHVef9VTgmByCyAM1VAhbAxcSZLMQLwsyx9LHe13\nfgz8BTgGLJYk6S/A14EMYOG1w16QJOlbsix/BPwS2N4HQ/eIdltu/PjxjB8/vg9HFFx6KgRDED5o\n73VcXBwAVqsVEDLR3whFnSf0lEAQmYSNgQsMBLZfK/V1BdhDR1UEI1AE1AEOYIEsy80AkiTNBV6R\nJOk64K/Asr4YuC/MZjMLFiyIOGVqsVjctiPXrFkDhMZ2pKB3UWS8oqKCXbt2qa8LmeifhJLOE3pK\nIIhMwsbAlWX5DKAXvX0JyNZ5HVmW/whM6MlxBQNF2UcaobwdKehdFBm32WzMnDlTyEQ/J5R0ntBT\nAkFkEjYGriD8CMXtSEHfImRCEGoImRQIIpNwa/QgCENCaTtSEBoImRCEGkImBYLIQnhwBT1OKG1H\nCkIDIROCUEPIpEAQWQgPrkAgEAgEAoEgohAGrkAgEAgEAoEgohAGrkAgEAgEAoEgohAGrkAgEAgE\nAoEgohAGrkAgEAgEAoEgohAGrkAgEAgEAoEgohAGrkAgEAgEAoEgohAGrkAgEAgEAoEgohAGrkAg\nEAgEAoEgohAGrkAgEAgEAoEgohAGrkAgEAgEAoEgohAGbj/BZrNRXFyMzWbr66EI+iFC/gT9GSH/\nAkHvIwzcfoIvBSsUsMAX3ZERIV+C/kxX5V88NwJB1xEGboRjs9moqamhpqYGQP1dqzCFIhX4oisy\n4q/8CQSRSHflX+hlgaDrGPp6AIKexWKxUFxcrP5/zZo1ACxYsIAFCxZgs9lUJQyo/5rNZsxmc+8P\nWBBydEdGfMmfQBDJdFX+hV4WCLpPWBm4kiQtB+YDg4AvgAeAz4EXgRlAC7BWluWSa+//d+D3wBDg\n78DPZFk+1wdD7zMyMzOZOnUqNTU1rFmzhpUrVzJ+/HhVSQoDROCL7siIL/kTCCKZrsq/0MsCQfcJ\nKwMXaAZSZFm+KknSaqAAeB+IBcYAiUCVJElHADtQCtwty/L/SJL0e+C/6TCK+w3aFf/48eMZP368\n+v+uKGCbzYbFYiEzM1MYKv2AQGVEKx/e5E8gCCahppu6Kv9iYSgQdJ+wisGVZXmTLMtXr/33b4AZ\n+P+ADXIHJ4E/Aj8C7gSqZVn+n2vvfwH4cW+POVQwm80sWLCgk4I0m81uSlf53ZeB6ysuLFxix8Jl\nnH1JoDKid009yZ+v43oLIQeRQbDuY7CTwvyRf+37A9XLAoHAnbAycDX8HNgGJAEnXV4/Bdyk8/pn\nwPWSJA3urQGGEr4UrL8GiL8JE+FiMITLOEMBXzLiTT6EgSvoSYKdzNjXBm53jxMIBOEXogCAJEn/\nDbTIsrxZkqT1wFWXP7e7/Ghfd/1X4IKiSL3hT1xYuCRHhMs4QwlfMhKOCTVCDiKDYMWsdlUeekqO\n/NHLAoFAn7AzcCVJ2giYgPuuvfQ58DU6PLdc+/094AJwl8uhCYBVluUrnj770UcfZdiwYW6vzZ07\nl7lz5wZl7OGOP3Fh4ZIc0Rvj3L17N7t373Z77YsvvgjKZ4ci4ZhQEy7yKvBOsGJWuyoPQo4EgtAj\nbAxcSZKi6AhJOCvL8nyXP70JLJYk6S/A14EMYOG1v70gSdK3ZFn+CPglsN3bOZ5//nm+/e1vB33s\nkYI/CRPhkhzRG+PUWxy98sorzJ8/38MR4U04JtSEi7wKvBOsZMauyoOQI4Eg9AgbAxeYA8wFTkqS\ndDcgAx8ADwKbgTrAASyQZbkZQJKkucArkiRdB/wVWNYXA480vMWFhUvWfLiMMxzpSkJNX90LIQeR\nRXdjVrsqD0KOBILQI2wMXFmWdwG7PPw528MxfwQm9Nig+in+xIWFS3JEuIwznOhq3GBf3gshB5FB\nsGJWRVKYQBD+hI2BKwgvwiU5IlzG2R/oy3sh5EDgSncXaQKBoO8J5zJhAkGPIkpH9R3i2gv6AiF3\nAkHkIAxcgcADYrLrO8S1F/QFQu4EgshBhCgIBBpEbdS+Q1x7QV8g5E4giDyEB7eXCCfPQDiNtSew\nWCzMnz9frWW5Zs0a5s+fj8Vi6eORdSbS7lVPXvtIu1aC4NEdueuuXAm5FAh6BmHg9hLhpMRCZax9\nNY7MzEx27tzJypUrAVi5ciU7d+4kMzOzV8fhD6Fyr4JFT177YLdfFUQO3ZE7b/Lhj+wI+RIIegYR\notDDhNPWV6iM1WazYbFYSElJobi4mKlTp/bq+cOhpmWo3Ktg0xPX3t9rpchdZmZmp9f7Qg4FvYc/\ncqeVD3/kypvsROozLBCECsLA7WHCqYVjqIy1traWwsJCcnJygL5T/KFc0zJU7lVPEcxr7++10hoj\nwgDpf3iTO618eJOrzMxMn7IT6c+wQNDXCAO3hwmnFo59PVbFoNixYwd1dXUUFBRgNBrJy8vDYDD0\nuuIP5ZqWfX2veppgXntf18qTIXvgwAF27fqqt4wwQCIfPbnzJB8ZGRke5cof4zXSn2GBoK8RBm4P\nEw7b3QrBGqunrV5fKJOC0+kkMTERh8NBXV0d999/P7m5uX2q+Lv6nXqKcJKrvsbXtbJYLGzatAm7\n3Y7JZCIvLw+73c6DDz7Izp07hQHSz/FkrM6bN4+YmBhSUlIAd7nyx3jtzjMcavpIIAhFRJJZLxHK\n291aujtWm83Gpk2b2LRpU0CJE0qiR15eHkajkUceeYTExETuu+++PjcsQjURJJzkyhO9dW09XavM\nzEzWrl3LwIEDcTqdPPTQQ1x33XX84Ac/cDM6lN/D+VoLAkebgJabm8vs2bO55ZZbVMNXK1dms9lv\n2enKMxyq+kggCCWEgdtLBMsQ6Q3F1tWxKtt4NTU1OJ1OSkpKqKys9Hus2kkhLS2N3NxckpOTA/4O\nwcL1OwHq76EysbhuqYbrhNeXBq6y/dza2srAgQP58ssvaWhowGAwYLVaqampQZKksF9ECLqO4mk9\nduwYTqeTgQMHUlpayokTJwCwWq1MnTrV47G+ZCcQfRvq+kggCCVEiEKYEcoZ3cpWr9PpxOFwcObM\nGXJzc8nOzmbOnDkcOXLEry01ReEnJyeTnp7eS6PXJ1wSQUJZLjyhGJeVlZU0NTVRWVkJ9G4Sl+v9\nbWlpobGxkfXr1xMbGxuy91rQe7hWdCktLeX73/8+f/rTn/zOEQh2HH+46KNw5tSpUwEvGKqrq3to\nNILuIAzcMEEv0cFut1NRUUF2dnZIGDWZmZk0NDRQUlLCmTNnGDVqFEajUS2WvnfvXr8MsFBK7gr1\nRJBwzvRXFkSNjY00NzeTn5+P0Wjs1cna9f7m5eXx2GOPAbBly5aQu9eCwOlurKprRZcLFy5w8OBB\nDAYDY8aMwel09nqOQKjro3Dn1KlTjBt3Cw7Hpb4eiiAICAM3TNBbuTscDi5cuMDMmTN7RcH5mizM\nZjOLFi3i9ttvJzc3F6PRyLJly9SSSxBeBhiEfjJXOHt0MjIykGWZvLw8ZFlm1qxZTJkyhaSkJKB3\nEmlc76/BYGD69OkAbNu2LeTutSBwurqzoVfRZfDgwQA4nU7a2tr49a9/TVFRkZoj0Bv0VJ1okbDW\ngc1mu2bc7gRuCeDIA8CqnhmUoMsIAzdM0HqaHnroIaDD09RbRqM/k4XZbGby5MlkZ2djsVior6+n\nsLBQ/fuaNWtwOp3ceuutFBQUhI1CDdVkLn88OqE4gdlsNl577TVKSkpobm6mvb2dN954g4MHD7Jo\n0SLGjRvXq2EX2vsbivda4D/d3dnQq+jy+eefc//99/PDH/6QZcuW8fnnn/PAAw/0SY5AMPVROIY3\n9Ty3AN8O4P0iRCEUEQZumOCqmO12O0VFRRiNRgwGQ4977TxNFpIk6cbVKp7c+Ph4MjIyyMrKcjPA\noqOjWb58OTabLWwUaiiFTbjiyaOjTFpKwflQm8AsFgsWiwWj0Uh8fDynT5/G6XSSmZlJRkZGp0Qa\n6NkFnPb+huK9FvhPd3c2tAvHnJwc1VubnJxMVlYWFouFV199tVfrhLsuVLsro+Ec3uSLrsTRgoil\njTSEgRsi+OtlM5vNLFmyhPT0dKxWa6/EYXmaLGbPnu0xrlZPATudTqKjo2ltbcVgMESUQu1rtB4d\npVTb6NGjaW1tBUJrAnM1IFauXMmYMWMoLCxk8uTJbvLmdDpZsmQJJpOJRYsWCcNT4BfdjVXVPiNK\nRZfhw4dTW1tLQ0MD0LvPVLAXquEc3uQNEUcrUAg7A1eSpAHA7bIsV/b1WIKJv8rLbDazdOlS4Cvl\n2tOxgtrJQkmoCCSu1mw2c+utt7J8+XIMBoMwXIKMYuC6lhGy2+1qLHRvePoDHa9r7Gt2djaTJ0/G\nbDZ3Mn4HDhzI2rVrmTx5csDnCcXwDEHP42+sqj95Ba4VXYqLiyksLKSuro7ExMReeaZ6ytMaqQlr\nXY+jBRFLG1mEjYErSdIgYAfwPSAGGHLt9WjgRWAG0AKslWW55Nrf/h34/bX3/h34mSzL53p98F7o\njvLqrbhQ17E4nU7eeOMNTp06hcHQIT7+KHmz2UxBQYH6XbtruAj0cfXKmEwmtWRbW1sbGzZsCLkJ\nTAlncTUwlH+jo6NxOBwYjUZaW1vVBZV2/N6MlFAMzxD0Hr50pFY+tLLkuhNls9lISUkhJyeHgoIC\nHA4HOTk5pKWl9Wgcbk95WkM9gbb7BBpHCyKWNrIIGwMXkIFtwJPA/7q8/gQQC4wBEoEqSZKOAHag\nFLhbluX/kSTp98B/Aw/05qB90R3l5SsOK9jeK8W7VlpaSn5+Pq2trQGt/AM1XIKBzWajpKQEIGTK\nqfUkWq9MXl6eGvPsbQLrK0+nJxlWSoi1tbURExPj9bnQM1JKSkrUMB7om/AM4T3uezzJlyfHQl1d\nHc888wwpKSmd7plr4tnly5fVXAilGY0S8x7se93TntZQTaAVCLpL2Bi4siy3AgckSfqa5k//H7BE\nlmUZOClJ0h+BHwGngWpZlv/n2vteAMoJMQO3J5SXa3Fyf7xX/kzEyoQwceJE9u7dS2trK9HR0Tid\nzoBW/r4Ml2AbBTabja1btwL0Wjm1vkTPK6N4SX3JgCIrQJ8bZhkZGTQ0NJCQkEBhYaHH6hB6Rord\nbmfDhg1s3boVo9EIBO71CoYcCu9x6KJ1LOTl5eF0OklJScFms1FVVYXJZHJLpFV09eHDh1m2bBk/\n+tGPVOM2WPdakbuMjAy3BN6e9LSGagKtQNBdwsbA9UIScNLl/6eAm4DBmtc/A66XJGmwLMuXe3F8\nXukJ5eVanBw8e68CMYT1PM1Kua9AFLovgz6YE0VtbS1VVVU4HA4ADh8+jN1uJzk5OeINDlevjLcJ\nTM9IjI6OZtOmTUFZGHUVWZbZu3cvTz/9NKD/XHgyUqZOnYrJZHIrpZeXlxfQwrE7chjJ2emRglYP\n3XbbbfzlL3/hb3/7GwAFBQUUFRVx9913884773SSA0mS+Ld/+zegQ9+67hR0pwGPInejR4/uJH/C\n0yoQBEYkGLjtwFXN/9s9vO76byceffRRhg0b5vba3LlzmTt3bnBG6oVgKC+94uTeWkn6awiDd8M0\nkJhITwa9Xo91T2PxB4vFwjPPPONWKuaxxx7DbDazYsWKXvFY7N69m927d7u99sUXX/T4ecF/r4zr\ntqvNZuPxxx9XC9n7ugc94aHUGoc2m43Zs2cjSVKn92pl8o477qCsrIzy8nIMBgPbtm1Tm6H4u3AM\nhnEaqdnpkYT2fo4cOZJBgwbRsREIV69e5cqVKzQ2NgIdcnDs2DG1K6PZbGbLli0899xzAMTGxgKe\nG/D4Wgy6tq12OBwcPXoUh8PRqX21kB+BwH8iwcD9HPgaHZ5brv3+HnABuMvlfQmAVZblK54+6Pnn\nn+fb3w40KD04BEN56RUn12sl6a8hrJdwoaBnMATiEdYa9P4aBf56DTMzM0lJSaGqqoqCggIAHnnk\nkR5PCHFFb3H0yiuvMH/+/F45vz+4brv+6le/YsCAAVx//fVe4167YgT6M8FbLBZaWlrYtWuX+rrS\nJCQ+Pp5x48a5HaM933333Udubq7bIiwuLo6Kigq/PdHBME4jNTs9ElH0UEZGBj/72c84fPgwjz32\nGN/5znc4fvw4H374oVqBRKnTPHHiRDf5ArBarWoDnpaWFn7/+9+7GadK2b6GhgbdcCFF7pqamrDZ\nbKrcr1q1itjYWJ/yJ+K9BYLOhKOBK137UXgTWCxJ0l+ArwMZwMJrf3tBkqRvybL8EfBLYHuvjrSX\n8Vac3NUYDcQQ1sZlZmRkePQ0B+IR1hr0/hoFgZRTM5vNmEwmioqKAJg+fXqEZQkHl6ioKLKzs4mP\nj2fLli0e70FXjEBf9035+8aNG5k5c2ZAxqEiS9rQE2URlp6e3ulcrsaA69iCYZxGfnZ65KDVQ3a7\nHbPZTHZ2NomJibpyoOwKud5XJTRB0TV2u538/HwMBoNqFDudTkpKSrj99tvVkngKitxVVlaSn5/P\nrFmz2LdvH8uWLev0Xj18GdACQX8kbAzca/VvPwGigIGSJH0KnAAygc1AHeAAFsiy3HztmLnAK5Ik\nXQf8FVjWF2PvLbQTq1KcXOux9GUIu4YLOJ1OCgsLmTJlihqXqZfFHkhohD9j1xoFXd06NpvNPPDA\nA+rvAndcFzuxsbG8/fbbOJ1O3W191wQYf41AX/dN+3er1YrJZFI9Y/4Yh1ojxVe4j2LQKglFrmNT\nvodyzu4YpyJmsm/ojjczOTmZFStWMGnSJK/6SHtfzWYzDz74IMnJyRw7dozCwkJmzZql7kiUlpbi\ncDg4c+YMubm5ZGdnuxmirnrMaDQyZcoUDh06xOTJk73Kn+vz482AFgj6I2Fj4Mqy3A542lvO9nDM\nH4EJPTaoEMXVo6X1Xil/92YIu3roHA4HL7/8Mm+//TaSJOkalv56hAMZe3e9hq6TnNIYQ9AZPY+l\np219V0+n66TrzQj0lpxYUFDg8b7Omzevy8ahp3AfrTG9Y8cOysrKMBgMnRphZGZmdts4FTGTfUN3\nYsP9WSzp3Vez2Ux8fDzr1q1Tk1r37duHwWDgG9/4BsePH+f06dPceOONGI1GLBYL8fHxup+zYMEC\nkpKS/JI/pSqNUu/akwEtEPRHwsbAFfiPvxOrJ0PYNX716aefVhMvhgwZouuV1ZZ08hQa0R0C3ToW\nJZr8Q7k2x44dcyv55ioPnrywkiT5nIT17ptSl9dmswWUvKhHIN46rTFdXl4OwB133EFlZWWncwvj\nNLxwTdRqamrqlKDVFQKRA9cwg1WrVqnhBZIk8ec//5klS5aoCylPusv1fOPGjVP1mCf5zszMpKGh\ngZKSEs6cOcOoUaO8GtACQX9CGLgRjL9tKPVet1gsFBUV0dLSwpgxY5BlmVOnTul6ZbUlnTyFRvg7\nZj3D1N+4RlGiKXB8yUl3m5Eon+l0OomOjqa1tRWDweAzJMDf+sz+LmT0mmCMHz8eu91OZWWliJUN\ncxQ5dTgc2Gw28vPzMRqNQale4Y8susp6bGysGiZgs9kYPHgwI0aMUJ+BQBZw3uTbbO6ocX377ber\nbbm9GdACQX9CGLgRTFe8mK5xlikpKezYsYPy8nIeeuihTl5ZTyWdhg8fHnAxfeX/vgxTX3GNokST\n/7jeP4PBwMSJE3W7ygUr8erWW29l+fLlui2e9UICvMmvVvYqKyspLS1lzpw5naotuI5Bb5Fks9l8\nxuyKDHV3QvGaTJw4kfT0dAYMGMCWLVuYNWsWU6ZMISkpqdufHYguddVRrvooNjYWu93O8uXLWbRo\nkc+qCP4u1M1mM5MnTyY7OxuLxSIWagLBNYSBG4F421J27Y6jPUZb4is9PR2TyURlZaWuV1ZrTHor\n6eRpnMq5ysrK/DJMfW0ZihJN/uPvYiAYVQHMZjMFBQWqXGrjfZXzgn+Tu3bs+fn51NXVAfDkk0/6\nHIurQetLpkSGemdCMQToT3/6E1u3buXGG28EOmJgDx06xIIFC/zSR3royaKvRg6u8qTVRxs2bPBL\nHwW6UFc8ufHx8Z0WiaG2EBEIegth4EYgnpTj7Nmz2bt3r+6kpC3xpXjE7rzzTo8Ja101JvUmjZSU\nFDZu3IjVau2WYRoMY6y/EOj9625VAO29iYuL49ChQ1gsFrei+P5M7p7KKiUkJFBTU+N1C9jfuEqR\nod6ZUAwBUsaUkJBAYmIi06ZN4/XXX2fhwoVMmzatW+PSk0W9Rg7a8QRSP1yPruhWPbkOxYWIQNBb\nCAM3AtEqRyVmVtl+dp2UAN0SX7/97W85daqjd4Ynj1ggyluvmL7T6cRut7slrik1d7trmHbXGAtX\nAvHYBDr5Bivxymw2M2/ePOrr6ykpKcFoNLrJpD+TuzL20tJS6urq2LdvH0ajUd1FCEZISl9kqIe6\nxy0UQ4Bcx2Q0GnnnnXc4f/48Z8+eDViHaK+/qywqjRygo/2zXsk7T41uAtVH3V2oh+JCRCDobYSB\nG2YEmuwAUF9fr0784D4pAW4lvi5evMiJEyf43ve+R1RUFAkJCVRUVFBRUcHdd9+tG+Lgj/LWK6a/\nZ88efvOb37Bw4ULuuece9fhgGKbBMsbCja54bPpiMdDS0sKqVavUzO+VK1fidDoZNmwYJSUlHsuQ\naeV/zpw5AGoFj9zcXOrr68nIyOj2GPsiQz3UPW59EQLkS+dpx7Rs2TLq6+tV2Qj0XK7X31WXKo0c\njEZjp7JyCxYs8Nnoxlc5Q2/hDoHEh9tsNh555BE+/vhj3Xj3/qgXQ53q6uqAjzGbzYwdO7YHRhM5\nCAO3D+iOl6YryQ4ZGRlkZWV5nJRcJ4eUlBT27NlDXV0dMTExFBYWqltyo0aN4plnniElJUXXwPU0\nXq0nQSnif/HiRZxOJ42NjWo4xLFjx9SkM2/lcQTudMdjE+zFgF6nsJKSEgA1EcZisWA0Ghk1apRq\nPH7nO9/BYrFw4sQJxo0bpzu5a+V/3LhxPPnkk27ft7CwkKysrG57Q5W4xkAz1Lty3nDxuPVFCJA/\nlQTMZjN2u52mpiaSk5PJztYtje72mVoZ9Xb9zWYzS5YsIT09vVMYlSRJVFRU8Pjjj3Py5MmAGt3o\nfTft2HzFh+sd//HHH7N27VpaW1sDXoiE+i5CZHEGGNCl9u1G4xA++aRaGLle6JKBK0lSIpAL3AFc\nDzQC7wKbZFluCt7wIpOuVjfw1RFKq5Q8KUftpOQ6huzsbG655RYSEhJYv3692lt927ZtvPvuuzQ2\nNnLkyBFMJpPXcyvobWlarVba29uJjo7GYDBQWlrK2bNnOXXqFB999JEaphDKnqxQw/U6O51OlixZ\ngslk8pmt3RNo5dtms7F161YAZs6c6VY3OT8/nxEjRnDfffdx7tw5JEni6NGjAGqxe+Uzvcm/JEnM\nnj3bLQwnOjpa7b7XnbjhQDPUu/J8h+LWvzd6w+vfk0a/9h75en7MZrPaMEYZhyILxcXFFBYWcvLk\nSW666SZkWfbZ6Mbbd9N7fvS8tHrJb9DRDdBgMNDa2kp0dLRbfeuuXBtBT9IMtAM7gVsCOK4ah2M+\nNptNGLheCNjAlSRpNvAqHW1z/0zHHYqno5vYEkmSMmVZ/nMQxxgxdMVIVfA1AfqjlDxNSjabjQMH\nDjBv3jwmTZrEXXfd5dZb/fz589hsNurr62lra2P9+vXs3LmTBx54gKVLl3o9t96WZkVFBX/4wx+4\ncuUKAwYMoLW1lfb2durq6rh48SJ79uwhJiYGp9MZsp6sUMP1Oq9cuZKBAweydu1aJk+e3Gtj0Cvd\n9eGHH/LZZ5+p3Z327NnDP//5T/72t7+Rn5+PwWDAZDLx7LPPIkkSABs2bGD9+vXMmjWLN954A/At\n/0eOHGHv3r1Ah4GycuVKHA4HbW1t3ZYhxZOrzVD39f0DOW+4Vf/ojRAgf41+5bpbrVZiY2OxWq0e\nEw1tNhu1tbXs2LHDTb+4tp/29fy46lGbzUZKSgo5OTkUFBQgyzJz587l9ddf99roxlOHv8zMTCZO\nnAh8JT92u71TFQ+945uaOnxLsbGxbp956623+u25DYddhMjkFuDbfT2IyEOWZb9/6GiVewF4WOdv\nErCKDoP3a4F8bl//0CFZclVVldyTbN68WU5LS+v0s3nzZlmWZbm6ulpOS0uTq6urOx3b1NQkV1dX\ny2+99ZaclpYmv/XWW3J1dbVcUVEhP/XUU/L27dvdXm9qavJ7XHrnbWpqktetWyeXl5fLP/3pT2Wj\n0SjHx8fLRqNRTkhIkCdMmCA/9dRT6phSU1PlhQsXyuXl5brndj2H8l3uvfdeecCAAbLJZJKNRqM8\nePBgOTo6Wo6OjpaHDBkijx07Vk5LS5NTU1Pln/zkJwF9p1Bl586dck/JWlNTk7x//345KSlJnjBh\nQpdkwdPnbt682efnrFu3Th47dqycmpoqp6WlyWPHjnW7n8r9NRgM8o033ihv375dfuqpp+SDBw/K\n+/fvl3Nzc+Xo6Gh5/vz58s033ywfOHDAbQx68q+MyfXvY8eOVa+BMhbX56yn8PV8+4M3HRAoPSlr\nvYGve64QyHXfvHmzPGHCBHnIkCHyhAkT3N6r9/yUl5fL69at8yj7rudWPnfcuHFu+krv+dH7bsuW\nLZNHjx6tymxqaqo8YcIEeeHChfKECRPkpKQkef/+/XJTU5Pu8eXl5XJ5ebnP6+WJ7shvKMlaVVWV\nDMhQJYMc4M/OLh7b28dVhcz17m2+usjXA6gAACAASURBVL98W/Zh2wXqwX0MeEuW5c06hrIMrJYk\nKQVYBvwiwM+OeDx5aSRJoqamxuvKWS/2zWw2s2zZMg4fPszXv/51NUYQ/Nva9LViV7bkAN5//33u\nuecenn/+eX71q18xffp0Dhw4wPz583E6nTQ1NbFt2zbKysrIzc1VvcraWDLXmLbs7GyOHDnCgw8+\nyFtvvcWsWbPYs2cP999/PzExMWzZsqVTa1fhSfCMkvXf1tZGTEyMKgvz5s0jJiamyzF1njz02vub\nnp7O1q1beeihh9i2bRurV69m4MCBfPbZZ2zevJnz588TFRXFhQsXiI6OVj24SsJWdXW1OvZhw4Zx\n5coVN0+ct9hP17+bTCbd+ENJkno0rjtYDTH6Y/UPPfyN9/X3umu9rRcvXiQlJYXs7GwmTZqk+/z4\nKgmm3TmZNGkSjz32GJMmTXILJ9CrqqD9bnFxcezfv199fu644w7ee+893nvvPdra2nSreGhbbEPn\nEAp/CbddBIHAF4EauNMBX/tSLwMbuzacyMaTwi4uLvY7/k6ZACVJorKykuPHj3PTTTepdUCV/uf+\nKCV/twCTk5PJzc1lzJgx7Nixg7S0NFXxpaen8/rrr7Nx40ZGjhxJTk4OY8aMYf369aSnp6uKffz4\n8Z2+y6RJk8jLyyMlJYV9+/bR0tLCoEGDuOeee4COUjza1q561zFS6G5yh6cJym63s3jx4oBj6vwJ\nqSkuLiYlJUXdIjYajQA4HA61dnJNTQ0bN27k0qVLjBkzhmHDhqmJZdnZ2WRkZFBTU8MHH3zAgAED\n2L9/P9dffz0rV67kwoULLFmyRA2FUUJpvIXhLFq0iMmTJ6vxuMpzVlNT06OxhcFIwOqNrf9ww5fR\n7+9115YTO3HiBHv27OGWW27hrrvucqutvGLFCn7xi1+oC21vnRWVBLdz585x9epVEhMT/UpcU36f\nN28edru90/Mza9Ys4uPjPVbxmDp1qq6+0IZQ9FTZQIEg1AnUwL0RqPfxnpPA6C6Npp+gVdiBrJzN\n5o7ajJs2baKkpITGxkZGjRrFG2+8wb/+9S/q6+t9ZhAr+HteZbw2m40VK1aQnJysZsZbrVZ2796N\n0+mkvb2doqIiHA4Hly5dIjc3l6amJiorK9XP0VPENpuNzMxMSktLycrKUt/jrbVrJBoB3U3u0F5f\npVqF1WoFAo+p87QAmjdvHjNnzqSyspKmpiaKi4t5//33MRgMGAwGtmzZwoULF6ioqCA9PR2z2czD\nDz/MxYsXmTBhAvn5+YwaNYrCwkImT56snsfhcDBy5EiioqKoq6tj9uzZHD9+XG0wYrPZ2LVrFzt3\n7vQZZ66gLAZ97ZAEE+GF7Rt8XXdXA3bt2rV873vfo76+3q05yPjx4zl58iSNjY289NJLDBs2TC0J\npsSzFhQUdNrJUPIT4Cv5OnDgALt27VLfp6e/zGYzMTExLF68WH2f8vxUV1frVvFQnmtPLbZdn4Gu\nLOqE/AoihUANXAPQ5uM9TmBg14YTngTqedNOwoGunPXKLI0cOZLp06d3qv3obWyBnlerOJ9//nkG\nDhzIgAEDMBgMnD17FkmSiIuL4/Tp02zatImmpiZ++9vfMnToUF3DVPFyTJw4kb1796rK2mzWb+0a\niVtmwU7uUO5TRUWFzwnWG54WQEpoisPhwGaz8be//Y2oqCjuuOMOKisrycvLc7tPZrNZbRaiTMrZ\n2dnqToNynsOHD/PYY4/x8MMPs2/fPlJTU6mtraW2tha73a7bqMTb9VGuQ3FxMZs2bcJut2Mymbq8\nUPL3ORde2ODi78LP13VX5KW0tJTPP/8cg8HA0KFD1RrhysKtrq6OIUOGcO+99xIXF0dRURFTp05l\nypQpPPvss26hUjabTXU2XLp0iba2NlauXKnK+M6dO33qL+1z5vr8mM2dq3j409Y8lMoGCgR9RVfK\nhJVIknTZy98Hd3Uw4Uqwyqr4u3LWxn25esPAvX5sd6or6KFVnFeuXOHSpUsMGDCA9vZ2zp49y9Wr\nV7nppptoaWmhtbWVhIQEFi9eTFJSUqfP8xUm0Z0ts3Cp5xjsElGunvGZM2d2eYHgaQEkSRLjx4/n\n6NGjFBYWcs899zBlyhQ1bMbbfVJCCLzdk/r6ei5evMjOnTsxGo2sWrVKNSpiY2O7ZKiPHj2aX/zi\nFzQ2NvK73/2OyZMnBxyT628ssiA49FRWv7Y5iN7CrbW1lbfeeksdx6FDh/jmN7+phkrZ7XYqKioA\ndGs6/8d//Ic6VuVZUJ4LRY5cW/l603PKM6NU8fBn5y3cys554tSpU+rC1l+60jRBEJkEauBu9/N9\n/wx0IOFIT3ne/Hmf8vlab5iyJaXERfozNu15PU3YNpuNhQsXUlFRgdlsZtiwYTQ2NtLS0gLAD3/4\nQ7KysvjTn/5EaWkpI0aMIDo6mrq6Op588kkWLFjAuHHj3M7tb1vWrsSUhUs9x2Ald2ivTbBi6hSD\ntrm5meLiYlpaWti1a5da+mvfvn0cOnSIefPm+Vwo6cm4a+tms9nMp59+yvDhw9Xt5NWrV6v33tUg\nCWRBpsRxnzlzhsuXL/tc/Lk2p7j77ruRZdlnLHKoy1m4oMhxS0sLW7duVY3GYBlp2uYgnhZu06ZN\nY8yYMbz22mv83//9n1sDB6fTyYULFygqKiIzM1Ot6aw4G0wmE4sXL1aT01yfC0/y4s3RoLfrp6A8\nC55aDIfr7tepU6cYN+4WHI5LfT0UQZgSkIEry/LPemog4Uhfr5JdvWGAW5zhjh07KCsrU+MiA62u\noKeAa2trOXr0KIMHD+bee+/lpZdeIioqipEjR3LlyhWysrL4wQ9+oLb3/eY3v8n777/P8uXLPSa+\n6RlhWmUdaExZuNVzDJYh2pWJ0x8U4+7cuXMUFxezceNGNQZ31apVbomNeufwVKheec1bclxlZSWT\nJ09Wk8QCvT5KZrzT6cTpdCLLMs888wwff/wx48eP9xgj7tqcoqWlRa2xC51jkcNFzsIFRY43btzI\n0KFDWbJkCVeuXPGri5y/n2+xWMjIyHB7Lo4cOaLGggO88cYbNDc3YzKZ+PrXv47D4eDkyZP86Ec/\n4t/+7d/YsmULJ06coLS0lBUrVmAwGPiP//gPTCaTW9z7+PHjdXW0Xrc0X13LlHEfOXLEbfzaZz9Y\nOqUvsdls14zbQJsgHKCjYqmgvxPxrXolSfp34PfAEODvwM9kWT4XjM/u61Wyq0LUVmIoLy8HUOMi\n/RmbJ8NQkiTOnTvHgQMHaG5uJioqioMHD1JfX09UVBSjRo1SDYcLFy6QkZHBN77xDY4dO8awYcNU\nA8V1aw5QDRzALTveNTvf9T3+Gq0lJSVs2LABk8kUsHHfl3TVEPVl0Hc1pk753MrKShwOB0ePHsXh\ncFBbW8vkyZNJTk4mNja20/1VJmDXMJlNmzZx4sQJ4uLiuPvuu3nttdewWCxqhQ29ydhms7ldj65c\nn8zMTBoaGtSEzDFjxnD58mVeeuklbrjhBs6fP09+fj5Go5EFCxaQmZlJbW0tVVVVqqETHR3Nr371\nK9ra2nS3tJ1OJ3a73a/WrALPuMpxS0sLa9asYfjw4UDHIsNqtXLLLbf4tXPjbZfH1Rh0vU+ZmZmk\npKRQXFxMc3MzTzzxBImJidTV1ZGfn8/ChQspLCzko48+orq6GqfTSUFBAadPn2bjxo3MmDGDoUOH\nuiWMueoeoFsOEWXco0ePVsefmZnpUWdrjeDwJdAmCCJEQdBBRBu4kiRdD5QCd8uy/D+SJP0e+G/g\ngWB8fiitkl2N7by8PO644w5mzZrFgQMHsFqtxMXFdfKMgvtk4MkjnZiYSHl5OWfPnqWtrY3GxkbO\nnDmDJElqmMKoUaPIysoiIyODEydO8I9//AODwcDUqVOpq6vjwIEDbmXDALffd+3axerVq9m0aRMJ\nCQkAVFVVUVRUREpKCsePH/d7ctDWYw2X7bmuGqLB3klw3SLetWsXVqsVq9XKc889x8CBA1m1ahWx\nsbGdQhK0E7BrmIzT6WT37t0YDAba29spKSnBYDBQWFjIfffdR3Jysvr9XWNjtduygX4fZZfDNRP9\n0UcfxWAw8I9//IMtW7Ywa9YspkyZQlJSEhaLhWeeecYt7k8JkXjwwQeBr55zs9nMzJkz1eS4X//6\n10yfPr1X5SyS4n9d5bihoYFPPvkESZIwGAycO3eORx99lMzMTHbu3On1c7zFSvtaCNpsNt5//31u\nuOEGpk2bpi5kbDYbX/va1/iv//ovVY/t2rWLG2+8kZtuuokPP/yQ+vp6cnJy1MQyRQ8r8g14dIh4\nu4+eFpqVlZXU19djsVjUSjN5eXmcPXuWb37zm1it1k5GfHeIJFkT9A8i2sAF7gSqZVn+n2v/fwEo\nJ0gGroJejFUgcaLBUBquxrbT6aSsrIwf/vCHHDp0iPb2dvVcWsXv+ponj3RpaSnHjx8nKiqKxsZG\n2tvbiYuLIz09XS3OX1hYSFJSEq+99ppb3caysjL+9Kc/cfnyZZ544gmcTieHDx8GOmo9Kr87nU5K\nSkrYs2cPo0ePZtCgQRQUFHDmzBl27NjBfffdx8aNG7FarR695a4tO13rScbFxYXd9lwgaO9bbm4u\n9fX1ZGRkdOnzXLeIZ86cyZ49e9QqCCNHjmT16tVuIQmffPIJmzZtYsSIEW4TcHFxMRUVFTidTlpb\nW7FarVy9elWNYRwxYgQvv/wy7777LkuXLlUN8mDXqzWb3TPRz549y969ezvFECse3JSUFKqqqigo\nKADgkUceIS0tjeHDh/ts19vbRFL8r+u1z8/PZ/DgwaSkpFBWVsbDDz/MjBkzdBNVFXwZsN4Wgq6e\nUIPBwB133MFHH33Eyy+/zNixYzGbzbS1takxtXfeeSe7d+9mxowZHD58WG2PqyzUxo8fr+rh3Nxc\n4KsdK23SmTJWT/dRGXdTU5Mahw6watUqTCaT2t53zZo13Hvvvbz44ot8/PHHmEymoIbNRJKsCfoH\nkW7gJtFRl1fhM+B6SZIGy7LsrRJEQOglafmjCJStW2WrNhgKyG63M2nSJI4ePcqePXu4dOkSUVFR\nHDhwgKFDh6r91+12O0CnWDFFOcNXCnjRokVkZWVx+PBhfv3rXxMbG0tmZiYzZ87kiSeeYO7cuWo9\nU9eM4tOnT2M2m9WyYQUFBVy6dIlly5YhSRJGo5HHHnsMWZbV7WLo2BI+ceIE8fHxqve4srKSBQsW\nkJKSQlNTk67Rqp3AlHqShw4d4vjx4xHredBOXmazmcLCQrKysgL6HK2BUFtby+XLl6mpqVFbH7a0\ntNDY2IgkSeo5X3vtNZ599lluuOEGmpub1Qn4/PnztLe38+WXX7pV2rh06RKSJGG1WjEYDNx2222k\npKTwySefeE3m6u41UjLRMzIyyMrKUmOIFy5cyNmzZ8nIyFDPZTKZKCoqAmD69OmqrLkmSWqT47Zs\n2cK2bduCEqLgzzZ7OMWZ+4NihBYVFXH27Fk1PKCtrY329nZmzpzp9XhfOxneQspcjzUYDFRWVvKH\nP/wBm82mhuIUFhbidDrVpLKhQ4eyZ88e7HY7RqORy5cvs3z5cjU8bNKkSXz44YfU1NQQHR3Npk2b\nVD3vGjvr6z661u/Nz89Xm/oocjtnzhzOnTvHxYsXOXr0qKrTo6KieOKJJxg0aBCLFi3qskxGoqwJ\n+geRbuC2A1c1/3f91yeBemP9VQTKllNJSQlGozEoSsN1pd/Q0MBLL70EdMRjrV27Vm2LumbNGpqa\nmgCIjY3F6XSyZMkSTCaTmrSmjX00mzu69ZjNZmbMmMHRo0eZN2+eW8knbfmyoUOHMmjQIC5fvqwm\naTQ3N6tJGkVFReTk5PDuu+/y9ttvc9NNN5GUlMSVK1cA+M53vkNtba3bRFRbW+vx+3uqJ9nVTl7h\nhiRJzJ49O+B6sQpaA2HVqlX861//UncAZFnm3LlzLF++nI8++kitU5yQkEBiYiJ33HEHe/bs4Z57\n7qG8vJxly5aRnJzMsWPHeOaZZ2hvb2fAgAGYTCaOHTtGVFQUY8aMobq6msWLF7slkkHwkzb1QhwU\nL9fRo0fdFgRms5kHHnhA/V2PnozB97VI7usE155C8eLu2LGD8vJyFi5cyB//+Ed+8pOf+HWst/vh\nLaRMG+L10EMP0dLSwrZt29y6RLqGBIwZM4aGhgauXr3Kl19+ycCBA5EkiZKSEi5fvsw3vvENDAYD\nK1euxOFw0NbW5pZ0ZjabWb9+vc98AddxG41GpkyZwqFDh0hMTOTll18mKyuLiooKGhsbqa+vR5Ik\n2tvb+de//sXw4cNZvHixmsfgCW/zXKTKmiDyiXQD9wvgLpf/JwBWWZav6L350UcfZdiwYW6vZWRk\nsHv3br+MI38VgWtxcGUrXykO3p2VtutK/+mnn2bUqFGcPHmSqKgo7r//foYOHcqrr77KypUr3bpc\nrVy5kgEDBjBlyhTVi6U3huHDh/Pzn/+chIQEPvroIzXGS8FVERsMBh544AHuueceNawgJyeHoqIi\ncnNzMZlMbNu2jenTpzNixAgOHjzI/PnzOXjwoDqRTJo0iVWrVrnFqVmtVmJjY7FarWr3IU8TWHc7\neXWX3bt3s3v3brfXvvjiix4735EjR3Sz/bva2GH16tU0NTVx/Phx/vCHP3D+/HmmTJlCbGws8+fP\n79T69L333uPs2bNcunQJo9GoJp8lJydjtVrZsWMHALfddhvHjx8nNTWVS5cusXTpUrUureLBDdRg\n7EqojyRJTJkyhbfffpuhQ4d2ko+lS5d6Pb4nYvD9XST3dYJrT+HqQVfi/rdu3erX9/L3fuglK7oe\na7fbKSoqwmg0EhMTw759+6irq6O+vl7dzVIM4Z///Od8+umnWCwWoKO2bmNjI7GxscyaNYvt27cz\naNAghg4dSkxMTKdnMpB8AWXcw4cP77SQTU9PZ+fOnZw4cYKCggJaW1sBePbZZ/nBD37gl3PG04Iq\nUmVNEPlEuoF7EHhBkqRvybL8EfBLvNTyff755/n2tzuyNbuyLeOvItDrRDZq1Ciys7N9rrS9oV3p\nNzQ0MGTIEAYNGqR6QN544w23LHW73Y7D4cBgMHDw4EHuuusuRowYofsd/TWgzGaz2i44OTkZk8kE\nQFpaGrm5uWrChdKDva2tjZEjRzJ06FAcDgfJyclkZ2e7ZdEH4kVQJoLudvLqLnPnzmXu3Llur73y\nyivMnz+/R87X3YlIK9uTJ0+mrKyMDz74gEuXOmpR1tfX88EHHzBx4kQWLVrktnU6c+ZMXn/9dVJS\nUvjGN76BJEnq5y5atIi//vWvVFRUcOjQIQYOHEhDQwPnzp3j//7v/3TbSwdiMAYaH2iz2Xjttdc4\nePCgmiTZ1UWmnsHUVfyV854wrkMJZUfIYrG4te/291hvdbM9LeCVvy1ZsoT09HR1Ya4suOfMmdPJ\nEH7ppZdobm4GoK2tjffeew/oCLN64403sNvtPPTQQ0ybNs3tmVTaRweSL6CMu7i42KMenj59OkVF\nRRgMBubNm+fTuPVnnot0WRNELhFt4Mqy3CxJ0lzgFUmSrgP+Cizz59iubMv4qwi8dSILRJF7qi9q\nt9uZOnUqZWVlTJo0iZEjRyJJEiNGjHBT/I888ohqvAwaNIjGxkZyc3PJzs5m0aJFHlfySuyia7KR\n9jrMnDmT+fPnuxU6T05OJj09XX2faw/22NhYXn31VS5cuEBFRQXp6eluE1EgxptyXHc7eYUbwZqI\nXA0EZcv4ueee4/Dhw8yYMYPy8nISEhLU7mL19fXU1dXxzjvvcOONN/L6668DEB8fr8asms1mvvWt\nb1FWVkZUVBQGg4Ho6GiGDx/O0KFDdc+v12lMK/NdjQ/01O46JSUl4OQ8bwZToAS6SAmmcd3T+Otl\nV+6p0r470J0X1/sRaMKiq+deOW9ycjIOh4MRI0ao4ztw4AAPPvggkyZN4sSJEzz55JN8+eWXxMTE\ncOnSJS5evMiQIUOYOnUqv/zlL5FlGfjqmdSWdVTyBRTd5w1fMqKE1mRnZwdt11G5NuEiawIBgJo8\n0p9/6CiyJ1dVVckKTU1NcnV1tfzWW2/JaWlp8ltvvSVXV1fLTU1Nsi+amprkzZs3+3xvdXW1nJqa\nKj/11FN+fa7e8WlpaXJ1dbX62ubNm+W0tLROP5s3b9Y99y9/+Us5KSlJHjJkiJyUlCRPmDBBTk1N\n7fR+V/bv3y8PGTJE3r9/f6e/BXLdAn3v5s2b5fLy8k7fuSvXqa/YuXOnrJW1YOOv/AXCU089JQ8Z\nMkSeMGFCJ7mqqamRn3rqKXn79u2691G5z9u3b5cnTJggP/TQQ7LRaJR/+9vfen2m9O6b9jWtvKem\npspjx46V161b5/X7uMrehAkT5KSkJLmoqEhOTU0NCTkJhsz2hqwFgr/fyV8d5o2mpia5vLxcXrhw\noZyamhqQ/nb9DD2do/0e1dXVclxcnBwdHS2PGTNGNhqNcnR0tHzzzTercqh9JrszvygEQ0aCMQ5Z\n7hlZq6qqkgEZqmSQA/jZ2cXjunNsbx9XFVLPdm/ylVzwbdmHbRfRHtzu0B1vmL8eHWXr1puHSg9v\nXitfq3vXYw0GA5MmTeLWW2/ld7/7HUaj0Wu3IOVYxXOnfI5SVNxbLV1PHgF/r7Fr6apAvQhms5l5\n8+Zx4MCBXou/7UuC6VFUmDNnDtARY6htl2s2m3VbnypoM9T37dvH1atXsdvtuvdbT77tdjvNzc3s\n27cPp9NJZWUlpaWl3HnnnWrd0TVr1vDQQw9RVFTk0wumlYO77rqLwYMHYzAYQiJLPJK8ZYF62YMR\n82mxWCgsLKSuro7ExMROekjbFcyTvlXGAVBZWcnJkyc7JXFKksSiRYu4ePEiJpOJp59+mszMTHJz\ncxk+fLjHms7d3W0JhoyI8ANBJCMMXB/01ETjyZD1FkuoLcCvoFXe3hSW1gBVSt/ceuutfP75514V\nnOuxStkcgNmzZ7N3716vtXS9XT9v11g7OWoT2zyhvb7akAlBYIwbN66TEavERmtbKntLUlm5ciWD\nBw/m4YcfVrdStegtkpqammhra+P8+fMkJiaSn59PXV0dAE8++aQaS97S0sKFCxeora3FZDK5Lb48\nhbN861vf4ujRo1RUVKjng77NEu+JRUpvoKfXAg336q7RZbPZSElJIScnh4KCAhwOBzk5OWotY6UJ\nibYrmF6uhLaqiLK4j42NdfseSp3oiooKYmNjyc3NJT093WeIRHfmFz0Z6Wpd9UhaUAkECsLA9UFP\nTTRaQ9YfL4e2AL83I9IfY8O1087w4cM5cuSIVwWn11BAGbsyZm0t3bi4OMrKyrwmz3m7xl0tUePa\n7lfUcAwe2gQeVxn2dB+V6xwdHY3D4WDo0KFMmzYNWZZVg8EVPTkbOHAgn332GZs3b+bLL79kxowZ\nXL16lYSEBCoqKli7di3nz59n27Zt2Gw28vPzMRgMjB07llOnTnk1MJRyZ/0lVrsn0Vugd9UjG4jR\n5akjo9FopK6uTq3ekpKSQmFhIfPnz+/UFUw5p6dxKx3tlGYLet8jOTmZFStWMHz4cGpqanzqnUDn\nl0DaEHfFwBUIIglh4PYyngzZAwcOePTKavuNW61WTCYTcXFxOJ1Ojh07xne/+12/FKergnXttDNu\n3Di3IvZ6KMcdO3YMh8PB66+/zueff662idSO2bX/eldr0AY6OWqv744dOygrK8NgMHisMynwHyUM\nRqnj3NTUpGscuKIkNFZVVWG32xk1alRAoSv19fVq1viVK1ewWq3s3LmTkSNHUlhYiMPh4Ny5c/zm\nN7+hvr6ewsJCpk2bxvDhw3nppZe4/vrrvS5sxDZt9/GnDa6Cv9c3EKPLU0fGvLw87r//fmbNmsUN\nN9zAjh07qKurY/369Vy4cIENGzYgSZLaftpT/VlALXvnKRTHdczFxcVs2rQJu92OyWQKmt7x1oa4\ntraWHTt2qM189L6DaLcr6E8IA7eX8eSRnDdvnlssoacuO9pjtKV0/I3hda20UFhY6NYv3ZeHwGKx\n8P3vf5/33ntP3Sp+8sknefrpp5k2bZp6nGv8mhJHWVFR4Vd2r0Kgk6P2WildhW677Tbeffddj5Uf\nBJ3xJEvKNXY4HKq31Gg0qgsbvcoeH3/8MY888gjPPfccgFqLuaKiQteLC18ZC0rnMSXEISMjg9TU\nVHbu3Ml//ud/8ve//50///nPPPfcc0iSxNWrV9m6dataCzQ6OtqvEmD+egy9hRf1V+PBn52WntgG\n1zOslTJcx44dAyA3N5eysjJWrVqF0+kkMTGRL7/8kubmZr773e/S2NjIsmXL1FrMSsys8r0yMjI6\nNb7x9T0yMzMZPXo0ubm5OJ1OtemMnrz4igPWfk+n0+mms5U5wlvMsevniHa7kUN1dXXAx5jNZsaO\nHdsDowk9hIHby3jzSHoy5PSOcW1i4FpKx263+1Rg2slo+/btqid36tSpHj0EitfO6XQSExPj9rrd\nbsdgMKhj1pbBWbNmDQ6HgwsXLgQcB6uU5Zk3b57P4/S6mcXFxfHSSy/R1NTkFj4h8I6nyTAjI4PR\no0dz9OhRCgsLmTVrFlOmTCEpKcntGOUzFJlRuixdvHiR6OhoAHbt2uVRHvQ8eEajkd/85jcAvPji\ni7z00kucPn2aMWPGYDAYuHjxIgMGDODKlSvExcVx+fJlTp8+zY033uhWZzrQ+qj+XJf+bDz4s9PS\nE9vgngzr2bNnu91f7fjuuece1q1bx8yZM3n11VfdvLOu8qv8rk0Q8xUeZbPZaG1txWg04nA4iI6O\n1vWmFhcXc9111/H0009z4sQJfv3rX+vKjuv3dDqdbjpbKeWnF3OsOC1Eu91I4wwwoEs11Y3GIXzy\nSXW/MHKFgdvL+PJI6nkHtMfExcXxwgsv8PHHH6vhAXl5eTidTlUxe1NgikKsqqqioKCAUaNGMX/+\nfK677jp1u1l7vGsbYCUGrb29vnElbQAAIABJREFUnf/6r/8CYMCAAfzjH//gwIEDJCUl6ba+hI56\nj4EqV5vNxq5du9i5c6dfcXvaa2W323nnnXcwmUyqkheK3TOeqhgo3vcjR46oHlyAffv2cfDgQTIz\nM5k4caJ6zLFjx7BYLNjtdlVmZFlm0KBBLF26lH//939X3wu+5cH12Th79iz33nsvJpOJLVu24HQ6\n+elPf4rBYKCwsJBBgwbxve99jx07dmA2mzvVme6KMerJSHDtwBbI94kkghnmEYgn3FtegMFgYOLE\nieoOgdK22+FwEBMTw8iRIxk8eDCzZ8+mublZjZl1Op0cPnwYwOt2vye0VUPa2tpYvny5unvg6ixw\nOBy89957NDU18corr5CRkaG7w6Sns3NyckhJSaGkpEQNb9PGHCvVRES73UijGWgHdgK3BHBcNQ7H\nfGw2mzBwBT2Hp20ub94B1799/PHHrF27ltbWVtasWcMdd9xBWVkZ5eXlPmNNFYO1qKiIM2fOkJiY\nyIsvvugxQ1jZelaaPPz2t78lISGBv/71r5w/f54BAwYQHR3Nli1b2LJlCz/+8Y/djFHX1pfaselt\naSt0x+tgNneUBtuzZw9vvvmm2q1KST7qTkvkSEdvMnQ4HDQ3N9PS0sKcOXPcGn4onZ4sFosaK7tm\nzRqcTieZmZkkJCSQn5/PrFmz2LdvH5MmTeL999/3S1a1xo7yd4vFwjvvvAN8NakXFhYSFRWFLMtE\nRUXxxz/+kdbWVm688Ua1m153ZMqTkeAal+n6en80HoIRhuBr8aGVCW28tlLdBTrfi4qKCi5cuMCr\nr75KbGwsL7/8MgCffvqpeg/Pnj3Lr371K6KionR1oS+0RveGDRvcvNmKHDU0NGCz2fj0009xOp1Y\nrVZycnKYO3duJ0+uns7etm0b27ZtcwtvU2KOXUPO9MYkEikjhVvoKOMv0MVXodz+8INOo4dQRK8o\n9/79++XU1FS5vLw8oILd2kLo27dvl/fv3++xWL9CdXW1PGHCBPnmm2+Wb775ZrmoqEh+/PHH5SFD\nhsiPP/64vH//frmmpsbtPOvWrZPLy8t1x+atWHl3C75v3rxZTk1NVQv5K80sutpYIxiEWvF9PVzl\nLDU1Vd64caO8ceNGedy4cXJSUpK8f//+TvfOW8F45X379++X09LSApJVT/KhHePChQvlAwcOqDI9\nZMgQOSEhQR41apTanGLz5s3dkilP37GmpiYoxfKDTTjImiv+Nh3QkwmlkYKve+HPPRw/frw8ZswY\necWKFV1uEuFpnK5j+OlPfyobDAbZYDDIkiTJ0dHRstFolEePHq0rj76aV/jT+KGnmt6IRg/hclz4\nN4gQjR4iFD0PklLDVkk2UPC1Rah4PkwmE5WVleq22KZNm3A6nbrHa5PTpk6dysSJE7n++usBmDJl\nCjNnzux0HqX1ZUVFBU1NTcTFxanbiN48ad31OgSrJXJ/w/Ue2O12fv/732MwGHA6nZw5c0Zt5zxn\nzhzVW+dri3rBggUkJSWpLZuV93qqAuK6jatXqcH1fAaDgdzcXLfzlZWVkZOTw7Zt2zrJTVdlyt9t\neFGFoWv42kb35X3X867qhYBBRyUYrZ6z2WxER0fT1tbG9ddfT3x8PE6nk7i4uG63vNa+rvytoqKC\n73//+2zdupW4uDiWLVvmFjurd5yis/0Jb/M1pv6cGCmIfISBG0b4k6DmScl5UmSSJKlZx76Unba+\nZGVlJZWVlcyePZsf//jHJCUl+Tzf1atX2bNnD3FxcV6bVSjfpTtxfVojKDs7Wxi3AWA2m1myZAlW\nq5U333yTM2fOMGrUKIxGIxaLhfj4eL/61bsaH+PGjcNms7F+/XpaWlqYMWOGWxUQBddKDU1NTTz+\n+OOMHDmyU2iJ3vmSk5PVmqfbtm3zaOQAnQwcfyZ7X+FFQr66hq8FrbdqMjExMboJg65VEXwZdRaL\nhU2bNtHW1kZMTAxbtmzhwoULVFRU+OyMp4e3cDPokNOlS5cyZswY/vCHPzB06FCmT5/uU8d1R86U\nY13rhPfXxEhB5CMM3BBDq3y9xZtpJ25vE7SnuDZZlvn44485ceIEra2tbokZ4G4M+FsBQns+5f9W\nq5UbbriBN998k9WrV7Nx40asVqtPT1p3DQezuXNL5P6OP8ac4n232WxkZGSQm5vr1s5Zz3jwNakr\n5/5//+//4XQ6WbJkiW57XNdKDQUFBciyzMKFC8nIyOg0Rm0ZJOV7AR7lRk+m/E088/Qd/fnuAs/4\n0m+e9I/dbmfx4sVuTXMUGdDTQ0qbcq2e64k4VW/PmauxqSTrejqXp1h07Xv8NVZra2spLCwkJycH\n6J+JkYLIRxi4IYZehzOt0vLmpdW+95NPPuG1114jISEB6OinXlpayp133skNN9ygZsgrxou3pB9/\nPKra8ynZ9KWlpQBcvHiR06dPs3z5cn72s5/xgx/8wONnuZ63O4aDMDw6E8hkaDabmTx5MtnZ2Vgs\nFvVe+WpDqnfO2tpaqqqqOHv2LOfPnyc/P58hQ4awcuVKLly4wJIlS1i6dClHjhxh06ZNXLx4kfb2\ndpqbm3nuueewWq0sWrTIqyGgjGn8+PFu3ipPi8aeKKEktn67jq+tfQXXUonw1X2z2+1s2rSJ0aNH\nq7WQXat66DWmcQ21UQhkx+iTTz5h9erVrFq1yq1hTm1tLc888wwpKSkePcjKQtIb3p7XQORXea/S\n8KKgoACj0UheXh4Gg6FfJkYKIhdh4IYIWiVVWVnJyZMnVQ+Dt3gzb/GKr732Gs8++yyJiYkYjUa1\nMcMHH3zA6dOnATCZTDidThwOB21tbZ2yfrV486hqz6fECX/961/nH//4Bw0NDUiShMFgwGKxEBMT\nI7Z1e5GuGnOKFzw+Ph5JkvxqQ6rFYrHwzDPPYLPZkGWZAQMG0NjYiCzLZGZm8tFHH2G1WrHZbGRm\nZtLQ0KBmucfHx3sNjfD2vXwtGnuihFJ/ronbXXwtSF3jV13DnFxLJeot2pWqHhMnTnTz0Gp3Irqy\nY3TixAneeust5s2bp4bh2Gw2qqqq1H9NJpNHp4Un/HleA5Ff5b1KwwuHw0FdXR3333+/WmJNIIgU\nhIEbImiV1KpVq7yW7dI71rWzlMFgUEs0JSYmMm3aNA4cOMDMmTN55513mDFjBomJiWp90ry8PKKj\no1m+fLlfCWqeDAzlfEpJKKVDUHNzM3//+9/Jy8ujubmZ//zP/1SbA/hqESwIHt0x5pT7rtfEw5/P\n0NbyhI6C/Hv27CE1NZXjx4/z5ptvqrVAFy1axO23394pNMJXfLgyJleDBjwvGjMyMoK2NS0K6vc8\nrlv7M2fOVO+ba6lEb4t25f572okIZMfnk08+4cSJExw9ehRA/besrIy3335brRVdUFDACy+8wOzZ\ns9V4Xn9kw5/nNZDQCu17c3JyKCoq4r777hOJkYKIQxi4IYJW8axevVpVxoWFhV6Vll5nqZaWFkpL\nSzEajRiNRl5//XUaGhrYvn07CQkJqmds9uzZAOpne9v+9YY2AW3fvn3U1dVRX19PdnY2xcXFvPji\ni0iShCRJ7Nu3j0OHDrFgwYIeNXDFVrE7eoXx6+vrO8W2BvIZ/hqEykRuMpkoKioCYODAgbS1tbF9\n+3ba2trcqjQsWrRINzTC3zEpW9JKbV5fi0a73a5W+ejqZC8K6vceWsPwvvvuIzc3162LoadFu5KA\n1pWdCAWbzUZ2djbHjx9HkiQACgsLKSws1NVp58+f55VXXlHrN3tLklPwt0Ocv6EV2vempaWRm5ur\nW7VBIAh3hIEbImgVj2vrSPCutPQ6SxkMBrKystTtuBUrVvDee+/x7rvv4nA4+N3vfqduz8XHx3fb\n+NMqYqX4/5w5c4AOI7yhoYERI0aQn5+vena9nTcYxqnYKnZHK2dmc0eXr6ysrC5/RleqW2RlZXH8\n+HF+/OMfM3ToUEpKSjh9+jRDhw5Vw1fi4+PJzMwkJiaG7Oxsn/evrKyMlJQUdUzf/e53ycrK6tKi\nsauIgvq9j+Jx1SuVqF20u+qUkpIS1q9fjyRJjBgxIuDFiM1m4+LFizz//PPU19ezYcMGMjIyyM7O\nJjExkRtuuIHDhw/z2GOP8cgjj5CWlgbQKbFWmySn/W6BGK/+hla4XrOuVIgQCMIBYeCGGFol5Y/S\ncu0ypnSWUoxHm82mxlvJssz+/fu5dOmSW290xdsQaNKQdtzwVX1JxfOmIMsye/fu5emnnyY2NlY1\n4L3RHeNUbBV7R5IkZs+e7THG2x+6EquoHJeVlcXevXu54YYb1FCEnJwcmpqa+M1vfsP06dNV+fWn\nTbOSzFNUVOSxNq+nRaMiJ1arldjYWKxWa5fbOXfX+BcEjjakwFUu9fIVFJ2Snp7O4MGDuXLlCk6n\nk7y8PI/VQVxx1S1Go1FNdmtvb+ef//wnt912m3rP7XY7ZrOZtLS0TqEJnpLk9OTOn2ctkNCKQN4r\nEIQrYWXgSpI0DmiUZdne12PpKTwpa1/HKIovNjaW5ORkysrKVAV98803s3TpUpxOJ5IkcfnyZZYu\nXcqCBQvUMlBdMQZ9lTRT3qN8ttPp5PXXX2fatGnqlp6nz+2uceq6VayUozKZTKJF7zWOHDmibt1D\n722l693buLg4vvjiCwYMGKB0FsRut2O32z1O/oqsZWRkIMuymsxz4sQJpk+f7nZOX4vGnggr6Krx\nLwgMm81GSUkJgOrl95YjoOihPXv20NLSgtPpBODLL7/k8uXLfiWBaeUlLy+PL7/8kuuvv75Tybvk\n5GRWrFjhFgKg1B4/dOiQ38+gMEgFgi7gq9VZKPwATwEngTZgsuZvjwCfASeAdYB07fWxwLvA58AH\neGnrRpi06vWF0q6yvLzcrR3junXrOrWrnTBhgrxu3TpZlrveEldp++it9ary2ampqfKoUaPkwYMH\ny+PHj5d/8pOfeGx9Gch4lHNoP8u1Jafy3ZUWs33J/9/euUdXVV/7/jNDiJHcqqE8VJCHSLFFSoev\nVsYFjx61o3js1TiUQiGOeiwVa6PWU62CPVqr5+L1waOeixY9lGdBytWqWAunFTgN3vhqa88B5Sq+\nWg1EU0usgQTm/WPvtV3Z2Xtn7531zvyMkUFYO+s3f3v9vmuuuX6P+YvK9qnFboua79xcOisGd9tO\nnDhRR4wYocOGDdPBgweriOjgwYMzx0eMGJFXA472brjhhoLaLvVaONv+NjY2hq6V3hIVrfmJs3X4\n+PHjc+rQ0eptt92mI0aMyGirqqpKKyoqtKqqSg8//HCtqqrSY489Vm+77bYe74nse2fOnDl6wgkn\n6OGHH57ZFrqQ/yzGbwZFPv9ZKrZVb1zOs616o8g2YDHQ5D4oImcC15AKUNuA3wIzgRXAMuApVT1b\nRC4B1gEnBFjnUHDm/8EnvV7nn38+U6dO7TIfzBkChtLnDWb3wq1YsYKtW7dSWVnZLY+us3L+ySef\n5O6772bIkCFcfPHFrF+/nl27dnWx4e6Vy1WffLsS5eptcX6vqqqivb2d6upqDhw4kHMDi75Ib4bS\ne5MkPnv7ZFVlxowZvPfee6xdu5Z+/fpxwQUXMH78eEaOHNltvmL2wqA9e/awf/9+Dh482MVOW1tb\nwWFmB/eow4knnkhnZydbt261lEkRx51T2Vl7sHnzZlpbW7vMxXX8w/XXX8+nPvUprrjiCpYuXcqc\nOXNoa2tj1apV9OvXj2uvvZa33367y6LEQj2qznzvzs5OJk+ezOc+9zkWLFhAe3s7V155Zc7tdrP9\nZnNzM7W1tZmpCkOHDs2MvAWFrVEwkkwsAlxV3Qwg3ce1LwFWqur76c8fAi4SkV8Ck4Dz0+c/IiKL\nROTzqvqHAKseKD0Ntbrng2VvXVpKsJNtp7GxEYBJkybR1NTULUDetGkTy5cv58CBA3R0dLB8+fJM\nsnEnN2T20KDbfq50PkCP0xiyt960Fe3dKWUo3Ysk8dkvHn/9619ZuHAhFRUViAh79uzh7rvv5uKL\nL2blypXd5stmpyh76aWXOOywwzj11FP5xS9+kXl5K7RwJ/s7OVuWQuoFsbGx0eZsRxx3TmWHG2+8\nkUGDBjF37tzMLmZNTU20t7fzhz+k3L4zLeHMM8+ktraWRx99FCDzwv+Nb3yjxxd9RzOLFy/mpJNO\nYv78+VRWVlJdXc3u3btZsmQJDQ0N3RZvFdpq2Llvggo2bY2C0ReIRYBbgDGkemYd3gSGAccDzar6\nseuzt9OfJTbA7aknNtd8MDfFBjvZdpzFGa2trTQ1NXUJkB988EE2bNhATU0NNTU1NDc3U1VVxVFH\nHcXjjz9OY2Mj9fX1mXyW8ImzFZG86Xx62pUoVz3LSYmVdEqZ2+dVknj3i8cxxxxDZ2cnbW1tvP/+\n+5x33nnU19dz8sknd6mf8wLU1tbWZYtnR3u7d++msbGRMWPGAD0v3Cl2FKJQCiejMH6m6MvOqXzw\n4EG+9KUvUV9fz2mnnZbR6t69ezNZMwDuv/9+Kioq2L59O/X19Vx++eXAJ/oo9KKfqwf229/+dub3\nW2+9lcsuu4xZs2bl9LH5/LOIoKqBBpuWzs7oC0QmwBWR24ELSc2tABBgr6qeXeC0Q8DBHP/PPp7r\nbxNHTw66p2Cm2GAnO2OCezV6doDsduo33XQTH330EfX19axfv57Ozk7uvPNOdu7cycyZMzPnZDvb\nXBsL5NuVKHuaQvb/S02JZXyCV0nicz3om5ubue666/jOd77D1KlTM3/r1uTOnTtZvXo1U6dOpba2\nFvhE407P3Y4dO7jppptobW2ltrY274O72FGIYnuCje74Ofzt3NtOTuX9+/fz8ssvM3r0aAYNGtQl\ns8xdd93VbeMZ5/xcW+Tme9EvFBROmTKFyspKGhoais5B60xJaGtr67IjWxDBpqWzM/oCkQlwVfUW\n4JYST3sHGOn6/0jgjfTxo0Wkv6p2pD8bkf4sL9dddx1HHnlkl2PTp09n+vTpJVardLzs7QhiBfeu\nXbv4yU9+wowZM7qtTs+ui/P5YYcdxle/+lXGjx/Pz372s8y82DPOOIMzzjiDXbt2ccstt3D77bd3\nyZFbyBln70oE3a+lFymxymHNmjWsWbOmy7F33nnHN3t+k329SkkSn90m2S9in/3sZ6mrq8v0wLp5\n5ZVXWLt2LaNGjQI+ybyQS3stLS2ceOKJNDQ0FEz91NMoRCkpnIr5vlHDz/p5Ofztnpe/ZcuWbvUV\nEc4//3z27NnDSy+91MWW4w+qq6uZPHkymzZtKio9Yb4X/UIjQp/+9KdLzkELZKY6uHdkCyLY7M0c\nfMOIC5EJcMtkPXC/iCwCDgBXAHNV9V0ReRH4FvDj9CKzN1X11UKF3XfffZmh0aDxsrejnJQyxT7w\n3Husv//++7z11lvs2rUrY7dQna666ira2tqYP39+znmxw4cPz+w0Vcwc4ZaWFjZu3Ngl0HHq6L6W\n7pRYQaYMy/VytGrVqi691VGiWA04+iolSbyTp3bChAldgtIZM2awceNG6uvrWblyZc5z165dy/z5\n8xk9ejSVlZVd2i/XtIMDBw5QXV1Ne3t7Jt9ztiYKaWr27Nls3769V71qUV+842f9vBz+duo5fPjw\nzFxpt0a3bNmS2Rkse4GrE3DOnj2bMWPG5AxASwn03Zrp7OzkueeeY9u2bVx66aUl+1z3YuDsxWbF\nBptevKQE0RliGGERiwBXRNYApwLHAo+IyH7gS6q6Kb2w7EWgAnhIVX+VPq0eWCYi3wP+BFwWQtV7\nJIjJ/sU4wmIfeMuXL+fhhx+mvb0dVWXDhg08//zzzJkzJ7Olai477h627N4Kx7E7WRWc65FrioHb\nGWdvApDvWrqzMsybN4/+/ftz5513cvrpp5d/URNIsRoo5WHufiFy/nUvLJw6dSozZ85k6tSpOYOP\nlpYWRo0axejRo7ngggtYv349FRUVOdtv+fLlLFy4kNraWiorK+no6OCGG27I7OgH0NTUxLp165g2\nbRrjxo3rpqlCOi2mVy3qi3eCqJ8Xw99OPZ1FYtu2baO9vZ0tW7awcuXKzItST7bcWs21fW4+zRfy\nmSLC5MmTeeKJJ6ipqSn5Gva02MzxZV757EKU0xliGHEhFgGuquadI6Cq84H5OY6/Dkzxs15eEMRk\n/0KOsJwH3sGDBzlw4ACqioiwf/9+mpub2bVrV48ON1fP2datWzPXYPDgwZkFIdnXwB185NpDfuPG\njXl73erq6ixlWB78DHrcL0QACxYsYMmSJVx66aWZbXTz2XTfG5WVlaxfv563336bgQMH5my/M844\ng4cffpgrrriCZcuWsXDhwsxiRKcH/6677mL37t0A/OAHP8j7gC93CDfqi3eCqJ8Xw9/Zi8QWLlyI\nqnLvvffy0UcfdcnAkivjSk/0pPlCge/atWt56qmn2LNnD8cccwzz5s2jsrKy6BGhQkG5Y6vQrpJR\nf4kyjKgQiwA3yfg52b8YR1jqA6++vp62tjaWLl1KR0cHw4YNY8CAATz22GPs27cvr51s3D1npV6D\nQj0gTmqp7HIsZVh+wgjKXn755R53cXLr4pprrqGiooKBAwcycODAbi8vLS0tNDc3U11dDUB7eztD\nhw7lqquu4tJLL+222GjUqFFFbcdb6hBu1BfvBFm/3gx/Zy8SO+6443jmmWeoqalhyJAhNDY20tTU\n1G0qQrG2CvmQXBldHJ1s2LCBDRs2UF1dzTHHHMO7777LMcccQ319fdH5awu9APjhsw2jz9LTThB9\n4YcI7GTm7G5Tyq5QPfHAAw9kdu6ZOHFizh12it3Ryr3jzd69e3X16tU6ePBgHTdunM6ZM0fHjx/f\nxUYxO6FlU+w16KnOucrpzc5dXhLF3aX8vDZO2YsXL9YBAwbo4sWLdceOHbpz584uNn/605/qbbfd\npjt37uxWxo4dO3TixIn65JNPFtwtL3uHNPduZrfddpsOGDCgy05Tpe6OVwp+3M+lUkhrUahfMTj1\nXL16tY4fP14XL16cU6Oltlk+zd9zzz0Fd1Hs7Q6J2X40u87F7OIYFV/mxnYyi8t5tpOZEQJ+TPav\nq6tj+PDh3VaUZ89rLWY4MXsThnPPPZerr76aDRs2MGvWLBoaGmhqasqZBaFYir0GPdU5VzleDJsm\nFT+vjVN2rk1GWlpaMqnmBg3Kn8Jt0KDUAsXTTz89Z9aMfBkR3N9p2rRpAIwaNYpFixYV7Ln0cm5j\nVHpus4l6/Rycep588sk0NDQwYcIEli1bljNHbSltlk/zzrzwfLmz3edVVlZSX19fkq/L9qPZPa7F\n9LCbLzOM4rAANyJ4Pdm/0Ipy9yItZyGDiGTSKWWX48ytfe+992hqasrU96qrruLoo4/ObI35+uuv\n58yCUCylXoN8D+lC5cTlwd4TfqR58vPa5NpkpKWlhXXr1nHWWWcVTOGW3Z6FXl46OzvZvn07r7/+\nOvX19Zm/GTduHD/4wQ+67Yzm1MNJRaXqTcL9qC/eiXr9HLIXiWXn2u7tfNRsv5d9Xr4XLxHhpJNO\nYtq0aTn9ab55s01NTezdu7eLHy03eE2KLzMMv7AAN6FkL9Dp6Ojg5ptv7rIQwt2bAKmHg6p2K2fR\nokW89tprQGqRTnV1dWa+l3vRlxPcurMgOGX4kW+znId0XB7sPeFHmic/r427bHdQsm/fPp566il+\n85vf5EzzVEodnfnca9asoV+/fjkzM+QKCpwUZq+99lom5RTY3MYokt3+vZ2P6rzQZPu9nnJnqyp/\n/OMfWbt2bSZdXaF70qlne3s7LS0t3fxovu9ZzPxwwzByYwFuzMnXa5A91LVw4cIumyM4AUZnZyeb\nN28GUr1fbkcOcNxxx3HRRRexdOlSPvjgAyZNmsRZZ53VJV+w+yGTnQVhypQpkc4HGjeSsILarZfa\n2lo6Oztpb2+no6Oji04Lka17Z6Rh4MCBdHR00NHRwebNm2ltbc2MMEDuQNtJYVZbW8sPf/jDzNa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QcWAk8Db5FyUiOBM4HZqvpEnOx4TdBtnkSNuQlSB1HUnN/tG/fy/cZPTYStN/NV3hB0OybF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\nhmEYhmEYicICXMMwDMMwDCNR/H8D54F5OPoVsAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb1c0c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 图示初判\n",
    "# （2）散点图矩阵初判多变量间关系\n",
    "\n",
    "data = pd.DataFrame(np.random.randn(200,4)*100, columns = ['A','B','C','D'])\n",
    "pd.scatter_matrix(data,figsize=(8,8),\n",
    "                  c = 'k',\n",
    "                 marker = '+',\n",
    "                 diagonal='hist',\n",
    "                 alpha = 0.8,\n",
    "                 range_padding=0.1)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     value1    value2\n",
      "0  0.438122  1.055646\n",
      "1  1.505379  1.515092\n",
      "2  1.508023  2.323125\n",
      "3  1.832305  3.552254\n",
      "4  3.406128  4.155919\n",
      "------\n",
      "value1正态性检验：\n",
      " KstestResult(statistic=0.095884626585008847, pvalue=0.29839852339800688)\n",
      "value2正态性检验：\n",
      " KstestResult(statistic=0.080469682048596169, pvalue=0.51965015851411267)\n",
      "------\n",
      "     value1    value2  (x-u1)*(y-u2)    (x-u1)**2   (y-u2)**2\n",
      "0  0.438122  1.055646    1292.819837  2814.467243  593.854178\n",
      "1  1.505379  1.515092    1242.927702  2702.366975  571.672643\n",
      "2  1.508023  2.323125    1200.861611  2702.092121  533.685953\n",
      "3  1.832305  3.552254    1129.876614  2668.483878  478.406924\n",
      "4  3.406128  4.155919    1065.219453  2508.361644  452.363990\n",
      "------\n",
      "Pearson相关系数为：0.9968\n"
     ]
    }
   ],
   "source": [
    "# Pearson相关系数\n",
    "\n",
    "data1 = pd.Series(np.random.rand(100)*100).sort_values()\n",
    "data2 = pd.Series(np.random.rand(100)*50).sort_values()\n",
    "data = pd.DataFrame({'value1':data1.values,\n",
    "                     'value2':data2.values})\n",
    "print(data.head())\n",
    "print('------')\n",
    "# 创建样本数据\n",
    "\n",
    "u1,u2 = data['value1'].mean(),data['value2'].mean()  # 计算均值\n",
    "std1,std2 = data['value1'].std(),data['value2'].std()  # 计算标准差\n",
    "print('value1正态性检验：\\n',stats.kstest(data['value1'], 'norm', (u1, std1)))\n",
    "print('value2正态性检验：\\n',stats.kstest(data['value2'], 'norm', (u2, std2)))\n",
    "print('------')\n",
    "# 正态性检验 → pvalue >0.05\n",
    "\n",
    "data['(x-u1)*(y-u2)'] = (data['value1'] - u1) * (data['value2'] - u2)\n",
    "data['(x-u1)**2'] = (data['value1'] - u1)**2\n",
    "data['(y-u2)**2'] = (data['value2'] - u2)**2\n",
    "print(data.head())\n",
    "print('------')\n",
    "# 制作Pearson相关系数求值表\n",
    "\n",
    "r = data['(x-u1)*(y-u2)'].sum() / (np.sqrt(data['(x-u1)**2'].sum() * data['(y-u2)**2'].sum()))\n",
    "print('Pearson相关系数为：%.4f' % r)\n",
    "# 求出r\n",
    "# |r| > 0.8 → 高度线性相关"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     value1    value2\n",
      "0  1.037320  0.379353\n",
      "1  2.098395  0.442863\n",
      "2  3.926912  1.104473\n",
      "3  4.427697  1.184688\n",
      "4  5.528188  1.213196\n",
      "------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>value1</th>\n",
       "      <th>value2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>value1</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.969122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>value2</th>\n",
       "      <td>0.969122</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          value1    value2\n",
       "value1  1.000000  0.969122\n",
       "value2  0.969122  1.000000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Pearson相关系数 - 算法\n",
    "\n",
    "data1 = pd.Series(np.random.rand(100)*100).sort_values()\n",
    "data2 = pd.Series(np.random.rand(100)*50).sort_values()\n",
    "data = pd.DataFrame({'value1':data1.values,\n",
    "                     'value2':data2.values})\n",
    "print(data.head())\n",
    "print('------')\n",
    "# 创建样本数据\n",
    "\n",
    "data.corr()\n",
    "# pandas相关性方法：data.corr(method='pearson', min_periods=1) → 直接给出数据字段的相关系数矩阵\n",
    "# method默认pearson"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    智商  每周看电视小时数\n",
      "0  106         7\n",
      "1   86         0\n",
      "2  100        27\n",
      "3  101        50\n",
      "4   99        28\n",
      "5  103        29\n",
      "6   97        20\n",
      "7  113        12\n",
      "8  112         6\n",
      "9  110        17\n",
      "------\n",
      "    智商  每周看电视小时数  range1  range2\n",
      "1   86         0       1       1\n",
      "8  112         6       9       2\n",
      "0  106         7       7       3\n",
      "7  113        12      10       4\n",
      "9  110        17       8       5\n",
      "6   97        20       2       6\n",
      "2  100        27       4       7\n",
      "4   99        28       3       8\n",
      "5  103        29       6       9\n",
      "3  101        50       5      10\n",
      "------\n",
      "    智商  每周看电视小时数  range1  range2  d  d2\n",
      "1   86         0       1       1  0   0\n",
      "8  112         6       9       2  7  49\n",
      "0  106         7       7       3  4  16\n",
      "7  113        12      10       4  6  36\n",
      "9  110        17       8       5  3   9\n",
      "6   97        20       2       6 -4  16\n",
      "2  100        27       4       7 -3   9\n",
      "4   99        28       3       8 -5  25\n",
      "5  103        29       6       9 -3   9\n",
      "3  101        50       5      10 -5  25\n",
      "------\n",
      "Pearson相关系数为：-0.1758\n"
     ]
    }
   ],
   "source": [
    "# Sperman秩相关系数\n",
    "\n",
    "data = pd.DataFrame({'智商':[106,86,100,101,99,103,97,113,112,110],\n",
    "                    '每周看电视小时数':[7,0,27,50,28,29,20,12,6,17]})\n",
    "print(data)\n",
    "print('------')\n",
    "# 创建样本数据\n",
    "\n",
    "data.sort_values('智商', inplace=True)\n",
    "data['range1'] = np.arange(1,len(data)+1)\n",
    "data.sort_values('每周看电视小时数', inplace=True)\n",
    "data['range2'] = np.arange(1,len(data)+1)\n",
    "print(data)\n",
    "print('------')\n",
    "# “智商”、“每周看电视小时数”重新按照从小到大排序，并设定秩次index\n",
    "\n",
    "data['d'] = data['range1'] - data['range2']\n",
    "data['d2'] = data['d']**2\n",
    "print(data)\n",
    "print('------')\n",
    "# 求出di，di2\n",
    "\n",
    "n = len(data)\n",
    "rs = 1 - 6 * (data['d2'].sum()) / (n * (n**2 - 1))\n",
    "print('Pearson相关系数为：%.4f' % rs)\n",
    "# 求出rs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    智商  每周看电视小时数\n",
      "0  106         7\n",
      "1   86         0\n",
      "2  100        27\n",
      "3  101        50\n",
      "4   99        28\n",
      "5  103        29\n",
      "6   97        20\n",
      "7  113        12\n",
      "8  112         6\n",
      "9  110        17\n",
      "------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>智商</th>\n",
       "      <th>每周看电视小时数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>智商</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.175758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>每周看电视小时数</th>\n",
       "      <td>-0.175758</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "                智商  每周看电视小时数\n",
       "智商        1.000000 -0.175758\n",
       "每周看电视小时数 -0.175758  1.000000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Pearson相关系数 - 算法\n",
    "\n",
    "data = pd.DataFrame({'智商':[106,86,100,101,99,103,97,113,112,110],\n",
    "                    '每周看电视小时数':[7,0,27,50,28,29,20,12,6,17]})\n",
    "print(data)\n",
    "print('------')\n",
    "# 创建样本数据\n",
    "\n",
    "data.corr(method='spearman')\n",
    "# pandas相关性方法：data.corr(method='pearson', min_periods=1) → 直接给出数据字段的相关系数矩阵\n",
    "# method默认pearson"
   ]
  }
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